Rumen fluid, feces, milk, water, feed, airborne dust, and bedding microbiota in dairy farms managed by automatic milking systems

Microbial dysbiosis in the gut–mammary axis as a mechanism for mastitis in dairy cows

Mastitis is a significant and costly disease in dairy cows, reducing milk production and affecting herd health. Recent research highlights the role of gastrointestinal microbial dysbiosis in the development of mastitis. This review focuses on how microbial imbalances in the rumen and intestines can compromise the integrity of the gastrointestinal barriers, allowing harmful bacteria and endotoxins, such as lipopolysaccharide, to enter the bloodstream and reach the mammary gland, triggering inflammation. This process links gastrointestinal health to mammary gland inflammation through the gut–mammary axis. Furthermore, disruptions in glucose metabolism and immune responses are implicated in the progression of mastitis. This review underscores the potential for non‐antibiotic interventions aimed at restoring microbial balance to reduce mastitis incidence, providing new insights into improving dairy cow health and farm productivity. Our findings emphasise the critical need to explore preventive measures targeting the rumen and intestinal microbiota for effective mastitis control.

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.

Evaluation of stirring time through a rumen simulation technique: Influences on rumen fermentation and bacterial community

Introduction

Rumen motility is a key element that influences ruminant nutrition, whereas little is known about the effects of rumen contraction duration on rumen fermentation and ruminal microbiome. We previously reported that proper rotation speed of a rumen simulation technique (RUSITEC) system enhanced rumen fermentation and microbial protein (MCP) production. In the present study, different contraction durations and intervals were simulated by setting different stirring times and intervals of the stirrers in a RUSITEC system. The objective of this trial was to evaluate the influences of stirring time on rumen fermentation characteristics, nutrient degradation, and ruminal bacterial microbiota in vitro.

Methods

This experiment was performed in a 3 × 3 Latin square design, with each experimental period comprising 4 d for adjustment and 3 d for sample collection. Three stirring time treatments were set: the constant stir (CS), the intermittent stir 1 (each stir for 5 min with an interval of 2 min, IS1), and the intermittent stir 2 (each stir for 4 min with an interval of 3 min, IS2).

Results

The total volatile fatty acid (TVFA) concentration, valerate molar proportion, ammonia nitrogen level, MCP density, protozoa count, disappearance rates of dry matter, organic matter, crude protein, neutral detergent fiber, and acid detergent fiber, emissions of total gas and methane, and the richness index Chao 1 for the bacterial community were higher (p < 0.05) in the IS1 when compared to those in the CS. The greatest TVFA, MCP, protozoa count, nutrient disappearance rates, gas productions, and bacterial richness indices of Ace and Chao 1 amongst all treatments were observed in the IS2. The relative abundance of the genus Treponema was enriched (p < 0.05) in CS, while the enrichment (p < 0.05) of Agathobacter ruminis and another two less known bacterial genera were identified in IS2.

Discussion

It could be concluded that the proper reduction in the stirring time might help to enhance the feed fermentation, MCP synthesis, gas production, and the relative abundances of specific bacterial taxa.

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.

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.

Influence of Dairy Cows Bedding Material on the Microbial Structure and Antibiotic Resistance Genes of Milk

The presence of pathogenic bacteria and antibiotic resistance genes (ARGs) in milk are among the most important issues related to the safety of dairy products and the health of consumers. However, despite that dairy cow are housed for long periods of time on different beddings, the effect of different bedding materials on the microbiota and presence of ARGs is unclear. In this study, the composition of microorganisms, and the presence of mastitis pathogens and 33 ARGs targeting seven antibiotics in raw milk produced from farms using sand bedding, rice husk bedding, and recycled manure solids (RMS) bedding were compared by amplicon sequencing and real-time quantitative PCR. The results showed that the microbial composition of milk was related to the microbiota of bedding. None of the mastitis pathogens were detected in milk from cows housed on sand bedding (S-M). The proportion of ARGs was highest in the S-M group and lowest in the milk from cows housed on RMS bedding (RMS-M) group. In general, the content of ARGs in RMS-M was the lowest, however, the RMS bedding may pose a threat to the breast health of dairy cows.

Nourishing the Human Holobiont to Reduce the Risk of Non-Communicable Diseases: A Cow’s Milk Evidence Map Example

The microbiome revolution brought the realization that diet, health, and safety for humans in reality means diet, health, and safety for the human holobiont/superorganism. Eating healthier means much more than just feeding human cells. Our diet must also nourish the combination of our microbiome and our connected physiological systems (e.g., the microimmunosome). For this reason, there has been an interest in returning to ancestral “complete” unprocessed foods enriched in microbes, including raw milks. To contribute to this inevitable “nourishing the holobiont” trend, we introduce a systematic risk–benefit analysis tool (evidence mapping), which facilitates transdisciplinary state-of-the-science decisions that transcend single scientific disciplines. Our prior paper developed an evidence map (a type of risk–benefit mind map) for raw vs. processed/pasteurized human breast milk. In the present paper, we follow with a comprehensive evidence map and narrative for raw/natural vs. processed/pasteurized cow’s milk. Importantly, the evidence maps incorporate clinical data for both infectious and non-communicable diseases and allow the impact of modern agricultural, food management, and medical and veterinary monitoring outcomes to be captured. Additionally, we focus on the impact of raw milks (as “complete” foods) on the microimmunosome, the microbiome-systems biology unit that significantly determines risk of the world’s number one cause of human death, non-communicable diseases.

Next-Generation Food Research: Use of Meta-Omic Approaches for Characterizing Microbial Communities Along the Food Chain

Microorganisms exist along the food chain and impact the quality and safety of foods in both positive and negative ways. Identifying and understanding the behavior of these microbial communities enable the implementation of preventative or corrective measures in public health and food industry settings. Current culture-dependent microbial analyses are time-consuming and target only specific subsets of microbes. However, the greater use of culture-independent meta-omic approaches has the potential to facilitate a thorough characterization of the microbial communities along the food chain. Indeed, these methods have shown potential in contributing to outbreak investigation, ensuring food authenticity, assessing the spread of antimicrobial resistance, tracking microbial dynamics during fermentation and processing, and uncovering the factors along the food chain that impact food quality and safety. This review examines the community-based approaches, and particularly the application of sequencing-based meta-omics strategies, for characterizing microbial communities along the food chain. Expected final online publication date for the Annual Review of Food Science and Technology, Volume 13 is March 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Temporal and geographical comparison of bulk tank milk and water microbiota composition in Brazilian dairy farms

This study investigated the relationship between the bacterial communities of bulk tank milk (BTM) and water used in Brazilian dairy farms. We also explored the association between BTM microbiota and its quality parameters (i.e., somatic cell count [SCC] and total bacteria count [TBC]). Water and BTM samples were collected twice for high throughput metataxonomic characterization. Milk samples were collected for SCCs, TBCs, and antimicrobial residue analysis. Water samples were submitted for physico-chemical and microbiological analyses. Overall, the BTM bacterial community was not influenced by the water microbiota. Furthermore, a higher number of Bacillus spp. and a tendency toward a higher number of Lactococcus spp. was associated with a higher TBC, and consequently could be used as an indicator of milk quality. A higher number of Streptococcus spp. and a tendency toward a higher number of Staphylococcus spp. were associated with a higher SCC. Apart from a variation on the content of the Bacillus taxa, no effect of sampling time on BTM bacterial community was observed. Finally, a negative correlation between the number of different species (richness) on BTM and SCC was found.

Microbial Characteristics and Safety of Dairy Manure ComPosting for Reuse as Dairy Bedding

Changes in bacterial community, phenotype, metabolic function, and pathogenic bacteria content in recycled manure solids (RMS) were analyzed by 16S rRNA sequencing, Bugbase, picrost2, and qPCR, respectively. The data from RMS bedding were compared to those of sand bedding and rice husk bedding. The results show that the proportion of potentially pathogenic bacteria among the manure flora of RMS after dry and wet separation, after composting, and after sun-cure storage was 74.00%, 26.03%, and 49.067%, respectively. Compared to RMS bedding, the proportion of potentially pathogenic microorganisms in sand bedding and rice husk bedding was higher. The picrust2 analyses show that the level of lipopolysaccharide biosynthesis changed significantly during RMS processing. In addition, the qPCR results show that composting could effectively reduce the detection and quantification of pathogens, except Streptococcus uberis, in RMS bedding. In general, composting is an essential step to improve the safety of bedding materials in the process of fecal treatment. However, at the same time, RMS bedding may increase the risk of mastitis caused by Streptococcus uberis.

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.

Effect of different seasons (spring vs summer) on the microbiota diversity in the feces of dairy cows

We aimed to study how seasonal heat stress (i.e., spring vs. summer) influenced microbiota diversity in the dairy cows' feces using Illumina MiSeq sequencing. Sixteen dairy cows were experiencing spring thermoneutral conditions (daily mean temperature = 18.8 ± 3.40 °; daily mean THI = 64.29 ± 4.94) and 16 under summer heat stress (daily mean temperature = 27.63 ± 5.34 °; daily mean THI = 82.56 ± 1.74). Fecal samples were collected per cow three times daily from day 18 to day 22 during each experimental period. Results revealed that the microbiota diversity in the feces was significantly lower (P < 0.05) under summer heat stress. At both the phylum and genera levels, significant differences were observed on microbiota composition in cow's feces between spring and summer. The most dominant phylum was Firmicutes, contributing 69.45% and 87.14% of the fecal microbiota in spring and summer, respectively, followed by Bacteroidetes, contributing 25.27% and 4.45%, respectively. Compared with the dairy cows in the spring season, the relative abundance of unclassified Peptostreptococcaceae, Turicibacter, and Clostridium_sensu_stricto_1 (P < 0.05) were greatly increased (P < 0.05), while the significant decrease in the proportion of Ruminococcaceae_UCG-005 and Rikenellaceae_RC9_gut_group as well as Bacteroides were observed in hot summer. Prediction of microbiota gene function in feces based on PICRUSt method found that different microbiota between spring and summer were mainly concentrated on the function related to membrane transport, infectious diseases, immune system diseases, and lipid metabolism. This study demonstrates that diversity and composition of fecal microbiota in dairy cows varies under different THI condition, and the relationship between fecal microbiota and cows' health needs further research.

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

Objective

The microbiota of dairy cow milk varies with the season, and this accounts in part for the seasonal variation in mastitis-causing bacteria and milk spoilage. The microbiota of the cowshed may be the most important factor because the teats of a dairy cow contact bedding material when the cow is resting. The objectives of the present study were to determine whether the microbiota of the milk and the cowshed vary between seasons, and to elucidate the relationship between the microbiota.

Methods

We used 16S rRNA gene amplicon sequencing to investigate the microbiota of milk, feces, bedding, and airborne dust collected at a dairy farm during summer and winter.

Results

The seasonal differences in the milk yield and milk composition were marginal. The fecal microbiota was stable across the two seasons. Many bacterial taxa of the bedding and airborne dust microbiota exhibited distinctive seasonal variation. In the milk microbiota, the abundances of Staphylococcaceae, Bacillaceae, Streptococcaceae, Microbacteriaceae, and Micrococcaceae were affected by the seasons; however, only Micrococcaceae had the same seasonal variation pattern as the bedding and airborne dust microbiota. Nevertheless, canonical analysis of principle coordinates revealed a distinctive group comprising the milk, bedding, and airborne dust microbiota.

Conclusion

Although the milk microbiota is related to the bedding and airborne dust microbiota, the relationship may not account for the seasonal variation in the milk microbiota. Some major bacterial families stably found in the bedding and airborne dust microbiota, e.g., Staphylococcaceae, Moraxellaceae, Ruminococcaceae, and Bacteroidaceae, may have greater influences than those that varied between seasons.

Microbial communities of the house fly Musca domestica vary with geographical location and habitat

House flies (Musca domestica) are widespread, synanthropic filth flies commonly found on decaying matter, garbage, and feces as well as human food. They have been shown to vector microbes, including clinically relevant pathogens. Previous studies have demonstrated that house flies carry a complex and variable prokaryotic microbiota, but the main drivers underlying this variability and the influence of habitat on the microbiota remain understudied. Moreover, the differences between the external and internal microbiota and the eukaryotic components have not been examined. To obtain a comprehensive view of the fly microbiota and its environmental drivers, we sampled over 400 flies from two geographically distinct countries (Belgium and Rwanda) and three different environments-farms, homes, and hospitals. Both the internal as well as external microbiota of the house flies were studied, using amplicon sequencing targeting both bacteria and fungi. Results show that the house fly's internal bacterial community is very diverse yet relatively consistent across geographic location and habitat, dominated by genera Staphylococcus and Weissella. The external bacterial community, however, varies with geographic location and habitat. The fly fungal microbiota carries a distinct signature correlating with the country of sampling, with order Capnodiales and genus Wallemia dominating Belgian flies and genus Cladosporium dominating Rwandan fly samples. Together, our results reveal an intricate country-specific pattern for fungal communities, a relatively stable internal bacterial microbiota and a variable external bacterial microbiota that depends on geographical location and habitat. These findings suggest that vectoring of a wide spectrum of environmental microbes occurs principally through the external fly body surface, while the internal microbiome is likely more limited by fly physiology.