No abstract

Studies have suggested that nanoscale extracellular vesicles (EV) in human and bovine milk carry immune modulatory properties which could provide beneficial health effects to infants. In order to assess the possible health effects of milk EV, it is essential to use isolates of high purity from other more abundant milk structures with well-documented bioactive properties. Furthermore, gentle isolation procedures are important for reducing the risk of generating vesicle artefacts, particularly when EV subpopulations are investigated. In this study, we present two isolation approaches accomplished in three steps based on size-exclusion chromatography (SEC) resulting in effective and reproducible EV isolation from raw milk. The approaches do not require any EV pelleting and can be applied to both human and bovine milk. We show that SEC effectively separates phospholipid membrane vesicles from the primary casein and whey protein components in two differently obtained casein reduced milk fractions, with one of the fractions obtained without the use of ultracentrifugation. Milk EV isolates were enriched in lactadherin, CD9, CD63 and CD81 compared to minimal levels of the EV-marker proteins in other relevant milk fractions such as milk fat globules. Nanoparticle tracking analysis and electron microscopy reveals the presence of heterogeneous sized vesicle structures in milk EV isolates. Lipid analysis by thin layer chromatography shows that EV isolates are devoid of triacylglycerides and presents a phospholipid profile differing from milk fat globules surrounded by epithelial cell plasma membrane. Moreover, the milk EV fractions are enriched in RNA with distinct and diverging profiles from milk fat globules. Collectively, our data supports that successful milk EV isolation can be accomplished in few steps without the use of ultracentrifugation, as the presented isolation approaches based on SEC effectively isolates EV in both human and bovine milk.

The objective of this study was to estimate genetic parameters of postnatal mortality (PM) in dairy cattle. Data originated from 841,921 Danish Holstein calves. Four binary traits of mortality were considered: D1-14, D15-60, D61-180, and D1-180 with numbers indicating the period of risk in days after birth. The unadjusted frequency of D1-14, D15-60, D61-180, and D1-180 were 0.027, 0.018, 0.020, and 0.066, respectively. A linear sire-model was fitted to the data, and average information-REML was used to estimate (co)variance components. Estimates of direct heritabilities for the four mortality traits ranged from 0.001 to 0.008 but were all significant. D61-180 and D1-180 had the highest direct heritabilities. Maternal heritabilities were very low, ranging from 0.0002 to 0.0015 and significant for D1-14 and D1-180 only. The direct genetic correlation between D1-14 and D15-60, between D15-60 and D61-180, and between D1-14 and D61-180 was 0.73, 0.54, and 0.34, respectively. It indicates that different genes are responsible for early PM (D1-14) and late PM (D61-180). When D61-180 was treated as a different trait for females, males not transferred, and transferred males, the direct heritability was 0.004, 0.008, and 0.034, respectively, but the direct genetic correlations between these three traits were very high. If transfers of calves are getting more common, the importance of including PM in a breeding program will increase, as the genetic variation of PM was considerably higher for transferred calves than for calves that were not transferred.

The primary aim of this study was to evaluate the phenotypic and genetic trends for stillbirth in Danish Holsteins. Trends of calving difficulty and calf size were also evaluated. The second aim was to compare predicted transmitting abilities (PTA) of sires for stillbirth using a linear and a threshold model. Direct and maternal genetic effects were modeled by fitting correlated additive genetic effects of the sire and the maternal grandsire (MGS). For both the calf and the dam, covariates of breed proportions of Holstein-Friesian (HF) and the heterozygosity between HF and the original Danish Black and White (ODBW) were included. Records from 1.8 million first-calving Danish Holstein cows calving from 1985 to 2002 were used. In this period, the overall frequency of stillbirth increased from 0.071 to 0.090. An unfavorable genetic trend of stillbirth was found for both the direct and maternal effect. The background for the genetic trends was an intense use of HF sires as sires of sons, which increased the proportion of HF genes to 94% in the Danish Holstein calves born in 2002. The effect of the imported HF genes was higher direct effects of calf size, calving difficulty, and stillbirth compared with the ODBW genes. The maternal effect of stillbirth was poorer for HF than for ODBW even though HF had a better maternal calving performance than ODBW. The threshold and the linear models showed almost similar predictions of transmitting abilities of sires.

The aim of this study was to explore the possibilities of using body condition score (BCS) or dairy character (DC) as indicators of mastitis and diseases other than mastitis in first-parity Danish Holsteins. The dataset included 28,948 observations on conformation scores and 365,136 disease observations. The analysis was performed using a multitrait linear sire model. Heritability estimates for BCS and DC were moderate (0.25 and 0.22), and heritability estimates for mastitis and diseases other than mastitis were low (0.038 and 0.022). Between BCS and diseases other than mastitis, the genetic correlation was -0.22, whereas the genetic correlation was -0.16 between BCS and mastitis. The genetic correlation between DC and diseases other than mastitis was 0.43, and between DC and mastitis it was 0.27. The genetic correlation between BCS and DC was -0.61. Residual correlations were close to 0, except between BCS and DC (-0.37). Including DC as an indicator of diseases other than mastitis will increase the accuracy of the predicted breeding value for diseases, especially when the progeny group is small. Using BCS as an additional indicator of diseases did not increase the accuracy. Breeding for less DC will increase resistance to diseases.