An investigation of seasonal variations in the microbiota of milk, feces, bedding, and airborne dust

Assessment of microbial communities in a dairy farm from a food safety perspective

Microbial communities associated with dairy farm operations have a significant influence on food safety, dairy product quality, and animal health. This study aimed to create a microbial mapping at a dairy farm to learn about their bacterial diversity, distribution, and potential dissemination pathways. The investigation included the detection of key zoonotic pathogens, enumeration of Staphylococcus aureus and Escherichia coli as indicators of typical bacterial loads in a dairy production environment, and a microbiome analysis using metagenomics. A total of 160 samples (environmental, udder swabs, feed, feces, raw milk, and water) were collected during winter (N = 80) and spring (N = 80). In winter, Cronobacter spp. were detected in four feed and two water samples; L. monocytogenes was identified in two samples, one from feces and one from a cattle mat; E. coli O157:H7 was found in two feed samples. On the other hand, during spring, Cronobacter spp. were present in four feed samples and one hallway drain, with only one feed sample testing positive for E. coli O157:H7, while L. monocytogenes was absent during the spring season. Regarding microbial counts, there was no significant difference between the two seasons (p = 0.068) for S. aureus; however, a significant difference (p = 0.025) was observed for E. coli. Environmental microbiome analysis showed the presence of Proteobacteria (46.0 %) and Firmicutes (27.2 %) as the dominant phyla during both seasons. Moraxellaceae (11.8 %) and Pseudomonadaceae (10.62 %) were notable during winter, while Lactobacillaceae (13.0 %) and Enterobacteriaceae (12.6 %) were prominent during spring. These findings offer valuable insights into microbial distribution within a dairy farm and potential risks to animal and human health through environmental cross-contamination.

Comparative study of the bacterial community of organic and conventional cow's milk

Agricultural practises such as conventional and organic farming can potentially affect the microbial communities in milk. In the present study, the bacterial diversity of milk was investigated using high-throughput sequencing on ten organic and ten conventional farms in the Azores, a region where milk production is largely based on year-round grazing systems. The microbiota of milk from both production systems was dominated by Bacillota, Pseudomonadota, Actinomycetota and Bacteroidota. The organic milk showed greater heterogeneity between farms, as reflected in the dispersion of diversity indices and the large variation in the relative abundances of the dominant genera. In contrast, conventionally produced milk showed a high degree of similarity within each season. In the conventional production system, the season also had a strong influence on the bacterial community, but this effect was not observed in the organic milk. The LEfSe analysis identified the genus Iamia as significantly (p < 0.05) more abundant in organic milk, but depending on the season, several other genera were identified that distinguished organic milk from conventionally produced milk. Of these, Bacillus, Iamia and Nocardioides were associated with the soil microbiota in organic farming.

Variations in milk, udder skin, and fecal microbiota and their relationships with blood metabolites and milk composition in dairy cows

This study examined the milk, udder skin, feces, and bedding microbiota in a dairy farm. Blood metabolites concentration and milk composition were also determined to examine their relationship with variations in the microbiota. Samples were collected from 10 healthy cows during the summers of 2018 and 2020. Milk protein, fat, and solid-not-fat contents were higher, and blood urea nitrogen and nonesterified fatty acid levels were lower in the 2020 samples. Principal coordinate analysis demonstrated that milk, udder skin, and fecal microbiota were separate groups. Year-to-year differences were distinct for milk and udder skin microbiota; however, the fecal microbiota of the 2018 and 2020 samples were similar. The bedding microbiota grouped with the udder skin microbiota of the 2018 samples. Although nonpathogens found as prevalent taxa in udder skin microbiota were likely to be found as abundant taxa in milk microbiota, selection and elimination occurred during transmission. Network analysis suggested that bacterial taxa of milk, udder skin, and fecal microbiota were unrelated to blood metabolites and milk composition, regardless of pathogens or nonpathogens.

Association of milk microbiome with bovine mastitis before and after antibiotic therapy

Background and Aim

Mastitis is recognized as the most common disease in cattle and causes economic losses in the dairy industry. A number of opportunistic bacterial taxa have been identified as causative agents for this disease. Conventionally, antibiotics are used to treat mastitis; however, most bacteria are resistant to the majority of antibiotics. This study aimed to use molecular methods to identify milk microbiome patterns characteristic of mastitis that can help in the early diagnosis of this disease and in the development of new treatment strategies.

Materials and Methods

To evaluate the microbiome composition, we performed NGS sequencing of the 16S rRNA gene of the V3 region.

Results

An increase in the abundance of the bacterial genera Hymenobacter and Lachnospiraceae NK4A136 group is associated with the development of subclinical and clinical mastitis in dairy cows. These bacteria can be added to the list of markers used to detect mastitis in cows. Furthermore, a decrease in the abundance of Ralstonia, Lachnospiraceae NK3A20 group, Acetitomaculum, Massilia, and Atopostipes in cows with mastitis may indicate their role in maintaining a healthy milk microbiome. Antibiotics reduced the levels of Streptococcus in milk compared to those in the healthy group and cows before antibiotic treatment. Antibiotic therapy also contributed to an increase in the abundance of beneficial bacteria of the genus Asticcacaulis.

Conclusion

This study expands our understanding of the association between milk microbiota and mastitis.

Influence of Technological Housing Conditions on the Concentration of Airborne Dust in Dairy Farms in the Summer: A Case Study

This research shows the size composition of airborne dust fractions in selected dairy barns down to the smallest particles, including factors that influence this composition. Measurements with a Dust-Track 8530 laser photometer took place in the summer at external temperatures of 29.5 to 36 °C. In barns with straw bedding, the average total dust concentration TDC was 66.98 ± 28.38 μg·m^-3 (PM₁₀ 60.11 ± 19.93 μg·m^-3, PM₄ 49.48 ± 13.76 μg·m^-3, PM_2.5 44.78 ± 10.18 μg·m^-3, and PM₁ 38.43 ± 9.29 μg·m^-3). In barns without straw bedding, the average TDC was 55.91 ± 36.6 μg·m^-3, PM₁₀ 33.71 ± 13.86 μg·m^-3, PM₄ 30.69 ± 15.29 μg·m^-3, PM_2.5 27.02 ± 13.38 μg·m^-3, and PM₁ 22.93 ± 10.48 μg·m^-3. The largest TDC of 108.09 ± 32.93 μg·m^-3 (PM₁₀ 69.80 ± 18.70 μg·m^-3, PM₄ 68.20 ± 18.41 μg·m^-3, PM_2.5 53.27 ± 14.73 μg·m^-3, and PM₁ 38.46 ± 5.55 μg·m^-3) was measured in an old cowshed with stanchion housing for 113 cows, straw bedding, and ventilation through windows. In a modern cowshed for loose housing of 440 lactating cows without straw bedding, with natural ventilation and 24 axial fans, TDC was 53.62 ± 49.52 μg·m^-3, PM₁₀ 20.91 ± 5.24 μg·m^-3, PM₄ 17.11 ± 3.23 μg·m^-3, PM_2.5 13.71 ± 0.92 μg·m^-3, and PM₁ 12.69 ± 2.82 μg·m^-3. In all investigated barns, a large proportion of airborne dust particles (54.38 ± 20.82% of TDC) consists of the smallest PM₁ dust particles (from 12.69 ± 2.82 μg·m^-3 to 48.48 ± 1.18 μg·m^-3).

Monitoring the Milk Composition, Milk Microbiota, and Blood Metabolites of Jersey Cows throughout a Lactation Period

This study aimed to determine how milk composition, milk microbiota, and blood metabolites may change during the lactation period in Jersey cows. Milk and jugular blood samples were collected from eight healthy cows every other month from the beginning to the end of their lactation period. Samples of airborne dust were also collected to determine whether the cowshed microbiota could affect milk microbiota. Milk yield peaked in the first two months and gradually decreased as the lactation period progressed. Milk fat, protein, and solids-not-fat contents were low in the first month, and then increased during the middle and late lactation periods. In the first month, plasma non-esterified fatty acids (NEFA), haptoglobin (Hp), and aspartate transaminase (AST) levels were elevated, and high abundances of Burkholderiaceae and Oxalobacteraceae were observed in milk and airborne dust microbiota. The finding that contamination of the environmental microbiota in milk was coupled with elevated plasma NEFA, Hp, and AST levels indicated that impaired metabolic function during the early lactation period may increase the invasion of opportunistic bacteria. This study can affirm the importance of feeding and cowshed management and should provide a helpful addition to improving Jersey cow farming.

A Low-Starch and High-Fiber Diet Intervention Impacts the Microbial Community of Raw Bovine Milk

Background

A more sustainable dairy cow diet was designed that minimizes use of feed components digestible by monogastric animals by increasing the quantity of forages.

Objectives

This study determined if feeding lactating cows the more sustainable, low-starch and high-fiber (LSHF) diet was associated with changes in raw milk microbiota composition and somatic cell count (SCC).

Methods

In a crossover design, 76 lactating Holstein cows were assigned to an LSHF diet or a high-starch and low-fiber (HSLF) diet, similar to common dairy cow diets in the United States, for 10 wk then placed on the opposite diet for 10 wk. The LSHF diet contained greater quantities of forages, beet pulp, and corn distillers' grain, but contained less canola meal and no high-moisture corn compared with the HSLF diet. Raw milk samples were collected from each cow 4-5 d before intervention and 5 wk into each diet treatment. Within 4 d, additional milk samples were collected for measurement of SCC using Fossmatic 7. The microbial community was determined by sequencing the 16S rRNA gene V4-V5 region and analyzing sequences with QIIME2. After quality filtering, 53 cows remained.

Results

Raw milk microbial communities differed by diet and time. Taxa associated with fiber consumption, such as Lachnospiraceae, Lactobacillus, Bacteroides, and Methanobrevibacter, were enriched with the LSHF diet. Meanwhile, taxa associated with mastitis, such as Pseudomonas, Stenotrophomonas, and Enterobacteriaceae, were enriched with the HSLF diet. Relatedly, an interaction of diet and time was found to impact SCC.

Conclusions

In raw milk, consumption of an LSHF diet compared with an HSLF diet was associated with changes in abundance of microbes previously associated with fiber consumption, udder health, and milk spoilage. Further research is needed to determine if an LSHF diet indeed leads to lower rates of mastitis and milk spoilage, which could benefit the dairy industry.

Source Tracker Modeling Based on 16S rDNA Sequencing and Analysis of Microbial Contamination Sources for Pasteurized Milk

Milk is rich in fat, protein, minerals, vitamins, peptides, immunologically active substances, and other nutrients, and it plays an important role in satisfying human nutrition and health. However, dairy product safety incidents caused by microbial contamination have occurred. We found that the total bacterial numbers in the pasteurized product were low and far below the limit requirements of the food safety standards of the European Union, the United States, and China. At the genus level, the primary microbial groups found in milk samples were Acinetobacter, Macrococcus, Pseudomonas, and Lactococcus, while in the equipment rinse water and air samples there was contamination by Stenotrophomonas and Acinetobacter. The Source Tracker model analysis indicated that the microorganisms in the final milk products were significantly related to the contamination in product tanks and raw milk. Therefore, it is the hope that this work can provide guidance to pinpoint contamination problems using the proper quality control sampling at specific stages in the pasteurization process.

The microbiome of common bedding materials before and after use on commercial dairy farms

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.

Supplementary Information

The online version contains supplementary material available at 10.1186/s42523-022-00171-2.

Effect of Peanut Shell and Rice Husk Bedding for Dairy Cows: An Analysis of Material Properties and Colostrum Microbiota

Simple Summary

The provision of appropriate bedding is important for the welfare of dairy cows. Before bedding can be selected, it is critical to understand the properties of the bedding, including its impact on milk microbiota. The objective of this article was to evaluate the influence of three materials for use as bedding on physicochemical properties, bacterial counts and colostrum microbiota of cows. Our results demonstrate that peanut shells appear to be a suitable bedding material for cows. These experiments provide empirical support for the use of peanut shells and rice husks as bedding material for dairy cows and illustrates the effects of bedding types on the colostrum microbiota of dairy cows.

Abstract

The aim of this study was to evaluate peanut shells and rice husks as bedding for dairy cows. We analyzed material properties including dry matter, water holding capacity, pH level and bacterial counts. Bedding treatments were compared with a one-way ANOVA using twelve cows split into three groups. Colostrum microbiota was analyzed by sequencing of the V3–V4 region of the 16S rRNA gene. Dry matter content was higher in rice husks compared with peanut shells. No treatment effects were found for water holding capacity and pH level. Streptococcus agalactia counts in peanut shell bedding were lower than in rice husk bedding, and Pseudomonas aeruginosa counts were not different between beddings. A significant enrichment for Enhydrobacter and Pantoea were detected in the colostrum of cows that used peanut shells compared with other beddings. Colostrum of cows housed on a peanut–rice combination had a greater relative abundance of Pseudomonas and Corynebacterium than those housed on peanut shells or rice husks. Higher numbers of Bacteroides, Akkermansia, Alistipes, Ruminococcaceae_UCG-014, Coriobacteriaceae_UCG-002 and Intestinimona were found in the colostrum of cows housed on rice husk bedding over other bedding types. These results suggest that bedding types were associated with the growth and diversity of colostrum bacterial loads. In addition, dry matter in peanut shells was lower than found in rice husks, but there was also a lower risk of mastitis for peanut shell bedding than other beddings.

Impacts of Milking and Housing Environment on Milk Microbiota

The aim of the present study was to determine the effects of farming environments on microbiota in raw milk and to assess the relationship among microbes by 16S rRNA sequencing methods. Samples of raw milk, cow trough water, teat dip cup, teat, teat liner, dairy hall air, cowshed air, feces, feed, and bedding from two farms were collected. The two highest abundant bacterial groups of Moraxellaceae and Staphylococcaceae were found in milk and teat liner samples, respectively, at Zhengzhou farm, Henan Province. Moreover, the two highest abundant bacterial groups of Enterobacteriaceae and Moraxellaceae were found in milk and teat dip cup samples, respectively, at Qiqihar farm, Heilongjiang Province. Source Tracker analysis revealed that the teat liner and teat dip cup were the most important contributors of microbes in milk samples at Zhengzhou farm and Qiqihar farm, respectively, which could be attributed to the management level of the farm. Therefore, disinfection and cleaning procedures should be developed to improve the quality of raw milk.

Examination of milk microbiota, fecal microbiota, and blood metabolites of Jersey cows in cool and hot seasons

Microbiota of individual cow milk, bulk tank milk, and feces of Jersey cows were examined. Samples were collected from two farms (F1 and F2) in cool (November, Nov) and hot (July, Jul) seasons. Milk yield and milk composition were similar between the two farms and between the two seasons. Prevalent taxa of the fecal microbiota, i.e. Ruminococcaceae, Bacteroidaceae, Lachnospiraceae, Rikenellaceae, and Clostridiaceae, were unaffected by the farm and season. Relative abundance of milk microbiota for Pseudomonadaceae, Enterobacteriaceae, and Streptococcaceae (F1 > F2) and Lactobacillaceae, Bifidobacteriaceae, and Cellulomonadaceae (F1 < F2) were different between the two farms, and those for Staphylococcaceae, Bacillaceae, Ruminococcaceae, and Veillonellaceae (Nov < Jul) and Methylobacteriaceae and Moraxellaceae (Nov > Jul) were different between the two seasons. The microbiota of bulk tank milk was numerically different from that of individual cow milk. Principal coordinate analysis indicated that the milk microbiota was unrelated to the fecal microbiota. The finding that relative abundance of Pseudomonadaceae and Moraxellaceae appeared greater than those reported for Holstein milk suggested that higher protein and fat content may result in a greater abundance of proteolytic and lipolytic taxa in Jersey cow milk.

Microbiota in Dung and Milk Differ Between Organic and Conventional Dairy Farms

Organic farming is increasingly promoted as a means to reduce the environmental impact of artificial fertilizers, pesticides, herbicides, and antibiotics in conventional dairy systems. These factors potentially affect the microbial communities of the production stages (soil, silage, dung, and milk) of the entire farm cycle. However, understanding whether the microbiota representative of different production stages reflects different agricultural practices - such as conventional versus organic farming - is unknown. Furthermore, the translocation of the microbial community across production stages is scarcely studied. We sequenced the microbial communities of soil, silage, dung, and milk samples from organic and conventional dairy farms in the Netherlands. We found that community structure of soil fungi and bacteria significantly differed among soil types, but not between organic versus conventional farming systems. The microbial communities of silage also did not differ among conventional and organic systems. Nevertheless, the dung microbiota of cows and the fungal communities in the milk were significantly structured by agricultural practice. We conclude that, while the production stages of dairy farms seem to be disconnected in terms of microbial transfer, certain practices specific for each agricultural system, such as the content of diet and the use of antibiotics, are potential drivers of shifts in the cow's microbiota, including the milk produced. This may reflect differences in farm animal health and quality of dairy products depending on farming practices.