Bovine colostrum whey: Postpartum changes of particle size distribution and immunoglobulin G concentration at different filtration pore sizes.

Bovine colostrum, as vital as it is for calves, is also a valuable source of functional components with rich health benefits for humans. Bovine colostrum whey consists of a large number of bioactive proteins and peptides. The most abundant of these is IgG. Particle size distribution (PSD) is an important feature of many of the processes in the dairy food industries. Despite this, scientific literature on PSD of colostrum whey is scarce. The goal of this research was to describe bovine colostrum whey PSD with an emphasis on postpartum milking time, filtration (pore size 450, 100, and 20 nm), IgG concentration, and lactation number. For this purpose, 4 postpartum milking colostrum samples were sequentially milked from 46 Holstein cows at 12 ± 1 h intervals. Colostrum whey was prepared by renneting and diluted (1:200) for PSD analyses by a Malvern Zetasizer Nano ZS (Malvern Instruments Ltd., Malvern, UK). Immunoglobulin G concentration of these diluted colostrum whey samples were analyzed by an Octet K2 (Molecular Devices LLC, San Jose, CA) system. Linear mixed model analysis revealed significant effects of filter pore size, postpartum milking, and lactation on colostrum whey IgG concentrations. The percentage of particles in the size interval 5 to 15 nm (the hydrodynamic diameter of IgG is around 10 nm) had an intermediate positive correlation (r = 0.50) with IgG concentration. Furthermore, we showed that PSD was associated with IgG concentration, postpartum milking time, and lactation number. The PSD measurement results showed the mean hydrodynamic diameter of 100 nm pore size filtered colostrum whey to be around 10 nm. This, with the IgG concentration results, suggests that even though the size of IgG is around 10 nm, a 100 nm pore size is adequate for membrane-involved IgG separations. In terms of energy efficiency of the filtration process, the use of a larger filter pore size can make a remarkable difference, for example, in pressurizing and cooling costs. Our work contributes to the development of sustainable and widely available colostrum-derived food and feed supplements.

Fatty acid profile of milk from Saanen and Swedish Landrace goats.

Recent years have had an increased demand for goat milk and its products. The quality of goat milk is determined, in part, by the fatty acid (FA) profile, but there is little information about breed influence on the FA profile of goat milk. The aim of this study was to describe and compare FA profiles of goat milk produced by Saanen and Swedish Landrace breeds. FA profiles were analysed by gas chromatography with a flame ionisation detector using 100 m capillary column coated with ionic liquids of extreme polarity (SLB-IL111). The amounts of 19 FAs were measured. Analyses indicated that FA profile in the milk of Saanen goats differs from that of Swedish Landrace goats with the first having higher proportions of most SFA-s and the second having lower proportions of C16:0, C16:1 and C18:1. This knowledge enables the improvement of the quality of goat milk and goat milk-derived products.

Adipose tissue insulin receptor and glucose transporter 4 expression, and blood glucose and insulin responses during glucose tolerance tests in transition Holstein cows with different body condition.

Glucose uptake in tissues is mediated by insulin receptor (INSR) and glucose transporter 4 (GLUT4). The aim of this study was to examine the effect of body condition during the dry period on adipose tissue mRNA and protein expression of INSR and GLUT4, and on the dynamics of glucose and insulin following the i.v. glucose tolerance test in Holstein cows 21 d before (d -21) and after (d 21) calving. Cows were grouped as body condition score (BCS) ≤3.0 (thin, T; n = 14), BCS = 3.25 to 3.5 (optimal, O; n = 14), and BCS ≥3.75 (overconditioned, OC; n = 14). Blood was analyzed for glucose, insulin, fatty acids, and ß-hydroxybutyrate concentrations. Adipose tissue was analyzed for INSR and GLUT4 mRNA and protein concentrations. During the glucose tolerance test 0.15 g/kg of body weight glucose was infused; blood was collected at -5, 5, 10, 20, 30, 40, 50, and 60 min, and analyzed for glucose and insulin. On d -21 the area under the curve (AUC) of glucose was smallest in group T (1,512 ± 33.9 mg/dL × min) and largest in group OC (1,783 ± 33.9 mg/dL × min), and different between all groups. Basal insulin on d -21 was lowest in group T (13.9 ± 2.32 µU/mL), which was different from group OC (24.9 ± 2.32 µU/mL. On d -21 the smallest AUC 5-60 of insulin in group T (5,308 ± 1,214 µU/mL × min) differed from the largest AUC in group OC (10,867 ± 1,215 µU/mL × min). Time to reach basal concentration of insulin in group OC (113 ± 14.1 min) was longer compared with group T (45 ± 14.1). The INSR mRNA abundance on d 21 was higher compared with d -21 in groups T (d -21: 3.3 ± 0.44; d 21: 5.9 ± 0.44) and O (d -21: 3.7 ± 0.45; d 21: 4.7 ± 0.45). The extent of INSR protein expression on d -21 was highest in group T (7.3 ± 0.74 ng/mL), differing from group O (4.6 ± 0.73 ng/mL), which had the lowest expression. The amount of GLUT4 protein on d -21 was lowest in group OC (1.2 ± 0.14 ng/mL), different from group O (1.8 ± 0.14 ng/mL), which had the highest amount, and from group T (1.5 ± 0.14 ng/mL). From d -21 to 21, a decrease occurred in the GLUT4 protein levels in both groups T (d -21: 1.5 ± 0.14 ng/mL; d 21: 0.8 ± 0.14 ng/mL) and O (d -21: 1.8 ± 0.14 ng/mL; d 21: 0.8 ± 0.14 ng/mL). These results demonstrate that in obese cows adipose tissue insulin resistance develops prepartum and is related to reduced GLUT4 protein synthesis. Regarding glucose metabolism, body condition did not affect adipose tissue insulin resistance postpartum.

Alterations in milk metabolome and coagulation ability during the lactation of dairy cows.

Milk composition has been known to change during lactation. To help understand the changes in metabolic profile throughout the whole lactation, liquid chromatography mass-spectrometry was used to analyze 306 milk samples from 82 primi- and multiparous dairy cows. Changes in metabolic profile common to all cows throughout lactation were ascertained based on principal component and general linear model analysis. Sets of specific markers; for instance, 225, 397, and 641-642 m/z (positive mode), and 186, 241, and 601-604 (negative mode), with at least a 1.5-fold higher intensity during the first 60 d compared with the last 60 d of lactation were observed. The metabolome was affected by parity and milking time. Markers, identified as peptides differentiating parity, were observed. A significant increase for citrate was observed in evening milk. Milk coagulation traits were strongly animal specific. The curd firmness values were influenced by milking time. Sets of markers were associated with curd firmness in positive (197 m/z) and negative (612, 737, 835, 836, 902, 1000, 1038, and 1079 m/z) ion mode.

Composite ß-κ-casein genotypes and their effect on composition and coagulation of milk from Estonian Holstein cows.

The objective of this study was to estimate the effect of composite ß-κ-CN genotypes on milk coagulation and composition traits, and on the additive genetic variation of these traits in Estonian Holstein dairy cattle. A total of 23,970 milk samples, repeated measurements from the first to third lactation from 2,859 Estonian Holstein cows from 78 herds across the country, were analyzed for milk yield, milk fat and protein percentages, somatic cell count, and milk coagulation properties (milk coagulation time and curd firmness). Each cow had at least 3 measurements per lactation. Two single-trait random regression animal models were fitted for the traits studied. The first model considered fixed effects of year-season of sampling and year-season of calving, calving age (nested within lactation), sample age (only for milk coagulation traits) and days in milk, and random herd, additive genetic, and permanent environmental effects. The animal and permanent environmental effects were modeled over the lactation period by using Legendre polynomials. The second model had the additional fixed ß-κ-casein effect in the form of a third-order Legendre polynomial. The 2 most frequent ß-κ-casein composite genotypes were A2A2AA and A1A2AA, both with prevalence greater than 20%. Percentages of the remaining 31 genotypes were less than 8%, including 20 genotypes with percentages less than 1%. The ß-κ-casein genotype-specific lactation curves were significantly different for milk coagulation traits and milk protein percentage. The B variant of κ-casein showed a favorable effect on both milk coagulation traits, whereas the IB haplotype had an increasing effect on curd firmness and protein percentage. Inclusion of the ß-κ-casein genotype effects in the model resulted in decreases in the mean additive genetic variations for milk coagulation time and curd firmness of 12.9 and 51.1%, respectively.

Comparison of the metabolic profiles of noncoagulating and coagulating bovine milk.

We hypothesize that, through milk composition and different milk metabolites, it is possible to characterize the technological properties (e.g., coagulation) of milk. In this research, liquid chromatography mass spectrometry was used to obtain profiles of low molecular weight organic compounds in 143 milk samples. The metabolic profiles of milk from cows were correlated with their coagulation properties. Using multivariate data analysis methods, we demonstrated that the metabolic profiles of the milk were correlated with coagulation ability. Several marker ions responsible for differential coagulation were found. Although not all affected metabolites could be identified, the most significant differences were found for carnitine and oligosaccharides. Exploitation of these results may increase the use of biomarkers to assess the coagulation ability of milk. This study represents the first large-scale metabolomic profiling of noncoagulating and coagulating bovine milk samples in Estonia.

Relationships between milk coagulation property traits analyzed with different methodologies.

Milk coagulation properties (MCP) analysis is performed using a wide range of methodologies in different countries and laboratories, using different instruments, coagulant activity in the milk, and type of coagulant. This makes it difficult to compare results and data from different research. The aims of this study were to propose a method for the transformation of values of rennet coagulation time (RCT) and curd firmness (a(30)) and to predict the noncoagulation (NC) probability of milk samples analyzed using different methodologies. Individual milk samples were collected during the morning milking in October 2010 from each of 165 Holstein-Friesian dairy cows in 2 freestall barns in Italy, and sent to 3 laboratories for MCP analysis. For each laboratory, MCP analysis was performed using a different methodology: A, with a computerized renneting meter instrument using 0.051 international milk clotting units (IMCU)/mL of coagulant activity; B, with a Lattodinamografo (Foss-Italia, Padova, Italy) using 0.051 IMCU/mL of coagulant activity; and C, with an Optigraph (Ysebaert, Frépillon, France) using 0.120 IMCU/mL of coagulant activity. The relationships between MCP traits were analyzed with correlation and regression analyses for each pair of methodologies. For each MCP trait, 2 regression models were applied: model 1 was a single regression model, where the dependent and independent variables were the same MCP trait determined by 2 different methodologies; in model 2, both a(30) and RCT were included as independent variables. The NC probabilities for laboratories with the highest number of NC samples were predicted based on the RCT and a(30) values measured in the laboratories with lower number of NC samples using logistic regression and receiver operating characteristic analysis. The percentages of NC samples were 4.2, 11.5, and 0.6% for A, B, and C, respectively. The transformation of MCP traits was more precise with model 1 for RCT (R(2): 0.77-0.82) than for a(30) (R(2): 0.28-0.63). The application of model 2 was needed when the C measurements were transformed into the other scales. The analyses of NC probabilities of milk samples showed that NC samples from one methodology were well distinguishable (with an accuracy of 0.972-0.996) based on the rennet coagulation time measured with the other methodology. A standard definition for MCP traits analysis is needed to enable reliable comparisons between MCP traits recorded in different laboratories and in different animal populations and breeds.