A.C.M. van Hooijdonk

Seasonal variation in the Dutch bovine raw milk composition.

In this study, we determined the detailed composition of and seasonal variation in Dutch dairy milk. Raw milk samples representative of the complete Dutch milk supply were collected weekly from February 2005 until February 2006. Large seasonal variation exists in the concentrations of the main components and milk fatty acid composition. Milk lactose concentration was rather constant throughout the season. Milk true protein content was somewhat more responsive to season, with the lowest content in June (3.21 g/100 g) and the highest content in December (3.38 g/100 g). Milk fat concentration increased from a minimum of 4.10 g/100 g in June to a maximum of 4.57 g/100 g in January. The largest (up to 2-fold) seasonal changes in the fatty acid composition were found for trans fatty acids, including conjugated linoleic acid. Milk protein composition was rather constant throughout the season. Milk unsaturation indices, which were used as an indication of desaturase activity, were lowest in spring and highest in autumn. Compared with a previous investigation of Dutch dairy milk in 1992, the fatty acid composition of Dutch raw milk has changed considerably, in particular with a higher content of saturated fatty acids in 2005 milk.

Effects of milk protein variants on the protein composition of bovine milk.

The effects of beta-lactoglobulin (beta-LG), beta-casein (beta-CN), and kappa-CN variants and beta-kappa-CN haplotypes on the relative concentrations of the major milk proteins alpha-lactalbumin (alpha-LA), beta-LG, alpha(S1)-CN, alpha(S2)-CN, beta-CN, and kappa-CN and milk production traits were estimated in the milk of 1,912 Dutch Holstein-Friesian cows. We show that in the Dutch Holstein-Friesian population, the allele frequencies have changed in the past 16 years. In addition, genetic variants and casein haplotypes have a major impact on the protein composition of milk and explain a considerable part of the genetic variation in milk protein composition. The beta-LG genotype was associated with the relative concentrations of beta-LG (A >> B) and of alpha-LA, alpha(S1)-CN, alpha(S2)-CN, beta-CN, and kappa-CN (B > A) but not with any milk production trait. The beta-CN genotype was associated with the relative concentrations of beta-CN and alpha(S2)-CN (A(2) > A(1)) and of alpha(S1)-CN and kappa-CN (A(1) > A(2)) and with protein yield (A(2) > A(1)). The kappa-CN genotype was associated with the relative concentrations of kappa-CN (B > E > A), alpha(S2)-CN (B > A), alpha-LA, and alpha(S1)-CN (A > B) and with protein percentage (B > A). Comparing the effects of casein haplotypes with the effects of single casein variants can provide better insight into what really underlies the effect of a variant on protein composition. We conclude that selection for both the beta-LG genotype B and the beta-kappa-CN haplotype A(2)B will result in cows that produce milk that is more suitable for cheese production.

Detection of Mastitis Pathogens by Analysis of Volatile Bacterial Metabolites

The ability to detect mastitis pathogens based on their volatile metabolites was studied. Milk samples from cows with clinical mastitis, caused by Staphylococcus aureus, coagulase-negative staphylococci, Streptococcus uberis, Streptococcus dysgalactiae, and Escherichia coli were collected. In addition, samples from cows without clinical mastitis and with low somatic cell count (SCC) were collected for comparison. All mastitis samples were examined by using classical microbiological methods, followed by headspace analysis for volatile metabolites. Milk from culture-negative samples contained a lower number and amount of volatile components compared with cows with clinical mastitis. Because of variability between samples within a group, comparisons between pathogens were not sufficient for classification of the samples by univariate statistics. Therefore, an artificial neural network was trained to classify the pathogen in the milk samples based on the bacterial metabolites. The trained network differentiated milk from uninfected and infected quarters very well. When comparing pathogens, Staph. aureus produced a very different pattern of volatile metabolites compared with the other samples. Samples with coagulase-negative staphylococci and E. coli had enough dissimilarity with the other pathogens, making it possible to separate these 2 pathogens from each other and from the other samples. The 2 streptococcus species did not show significant differences between each other but could be identified as a different group from the other pathogens. Five groups can thus be identified based on the volatile bacterial metabolites: Staph. aureus, coagulase-negative staphylococci, streptococci (Strep. uberis and Strep. dysgalactiae as one group), E. coli, and uninfected quarters.

Protein, casein and micellar salts in milk: Current content and historical perspectives

The protein and fat content of Dutch bulk milk has been monitored since the 1950s and has increased considerably, by 11 and 20%, respectively, whereas milk yield has more than doubled. The change in protein and fat content of milk is advantageous for the dairy industry, as these are the 2 most economically valuable constituents of milk. Increases in protein and fat content of milk have allowed increases in the yield of various products such as cheese and butter. However, for cheese and other applications where casein micelles play a crucial role in structure and stability, it is not only casein content, but also the properties of the casein micelles that determine processability. Of particular importance herein is the salt partition in milk, but it is unknown whether increased protein content has affected the milk salts and their distribution between casein micelles and milk serum. It was, therefore, the objective of this research to determine the salt composition and protein content for individual cow milk and bulk milk over a period of 1 yr and to compare these data to results obtained during the 1930s, 1950s, and 1960s in the last century. Calcium, magnesium, sodium, potassium, and phosphorus content were determined by inductively coupled plasma atomic emission spectrometry and inorganic phosphate, citrate, chloride, and sulfate content by anion-exchange chromatography in bulk milk and milk ultracentrifugate. In addition, ionic calcium and ionic magnesium concentration were determined by the Donnan membrane technique. We concluded that historical increase in milk yield and protein content in milk have resulted in correlated changes in casein content and the micellar salt fraction of milk. In addition, the essential nutrients, calcium, magnesium, and phosphorus in milk have increased the past 75yr; therefore, the nutritional value of milk has improved.

Phosphorylation of αS1-casein is regulated by different genes

Casein phosphorylation is a posttranslational modification catalyzed by kinase enzymes that attach phosphate groups to specific AA in the protein sequence. This modification is one of the key factors responsible for the stabilization of calcium phosphate nanoclusters in casein micelles and for the internal structure of the casein micelles. α(S1)-Casein (α(s1)-CN) is of special interest because it constitutes up to 40% of the total casein fraction in milk, and it has 2 common phosphorylation states, with 8 (α(S1)-CN-8P) and 9 (α(S1)-CN-9P) phosphorylated serine residues. Factors affecting this variation in the degree of phosphorylation are not currently known. The objective of this research was to determine the genetic background of α(S1)-CN-8P and α(S1)-CN-9P. The genetic and phenotypic correlation between α(S1)-CN-8P and α(S1)-CN-9P was low (0.18 and 0.19, respectively). This low genetic correlation suggests a different genetic background. These differences were further investigated by means of a genome-wide association study, which showed that both α(S1)-CN-8P and α(S1)-CN-9P were affected by a region on Bos taurus autosome (BTA) 6, but only α(S1)-CN-8P was affected by a region on BTA11 that contains the gene that encodes for β-lactoglobulin (β-LG), and only α(S1)-CN-9P was affected by a region on BTA14 that contains the diacylglycerol acyltransferase 1 (DGAT1) gene. Estimated effects of β-LG protein genotypes showed that only α(S1)-CN-8P was associated with the β-LG A/B polymorphism (g.1772G>A and g.3054C>T); the AA genotype of β-LG was associated with a lower concentration of α(S1)-CN-8P (-0.32% wt/wt) than the BB genotype (+0.41% wt/wt). Estimated effects of DGAT1 K232A genotypes showed that only α(S1)-CN-9P was associated with the DGAT1 gene polymorphism; DGAT1 AA genotype was associated with a higher α(S1)-CN-9P concentration (+0.53% wt/wt) than the DGAT1 KK genotype (-0.44% wt/wt). The results give insight in phosphorylation of α(S1)-CN-8P and α(S1)-CN-9P, which seem to be regulated by a different set of genes.

A proteomic perspective on the changes in milk proteins due to high somatic cell count

Although cows with subclinical mastitis have no difference in the appearance of their milk, milk composition and milk quality are altered because of the inflammation. To know the changes in milk quality with different somatic cell count (SCC) levels, 5 pooled bovine milk samples with SCC from 10(5) to 10(6) cells/mL were analyzed qualitatively and quantitatively using both one-dimension sodium dodecyl sulfate PAGE and filter-aided sample preparation coupled with dimethyl labeling, both followed by liquid chromatography tandem mass spectrometry. Minor differences were found on the qualitative level in the proteome from milk with different SCC levels, whereas the concentration of milk proteins showed remarkable changes. Not only immune-related proteins (cathelicidins, IGK protein, CD59 molecule, complement regulatory protein, lactadherin), but also proteins with other biological functions (e.g., lipid metabolism: platelet glycoprotein 4, butyrophilin subfamily 1 member A1, perilipin-2) were significantly different in milk from cows with high SCC level compared with low SCC level. The increased concentration of protease inhibitors in the milk with higher SCC levels may suggest a protective role in the mammary gland against protease activity. Prostaglandin-H2 D-isomerase showed a linear relation with SCC, which was confirmed with an ELISA. However, the correlation coefficient was lower in individual cows compared with bulk milk. These results indicate that prostaglandin-H2 D-isomerase may be used as an indicator to evaluate bulk milk quality and thereby reduce the economic loss in the dairy industry. The results from this study reflect the biological phenomena occurring during subclinical mastitis and in addition provide a potential indicator for the detection of bulk milk with high SCC.

Influence of C16:0 and long-chain saturated fatty acids on normal variation of bovine milk fat triacylglycerol structure

Fatty acids (FA) are nonrandomly distributed within milk fat triacylglycerols (TAG). Moreover, the structure of milk fat TAG differs with feeding regimens. So far, nothing is known about the variation of milk fat TAG structure among individual cows. A deep understanding of the normal variation of TAG structures and the relationships between milk fat FA profile and its TAG structure could help to better control functional and compositional differences between milk fats from various sources and to increase the knowledge on milk fat synthesis. The focus of the present study was to determine the regiospecific TAG structure of individual samples of winter milk fat from Dutch Holstein-Friesian cows with a wide variation of FA profiles and with 2 diacylglycerol acyltransferase 1 (DGAT1) genotypes: DGAT1 K232A genotype AA and DGAT1 K232A genotype KK. From an initial set of 1,918 individual milk fat samples, 24 were selected. The selected samples had a wide range of FA composition and had either DGAT1 K232A genotype AA or KK. The structure analysis was done with a regiospecific approach. This analysis is based on the acyl degradation of TAG by a Grignard reagent and further isolation of sn-2 monoacylglycerols by thin-layer chromatography. An intra- and interpositional approach was used to study the structural variation. With the intrapositional approach, the amount of an FA at the secondary (sn-2) and primary (sn-1,3) positions was related to its total amount in the TAG. With the interpositional approach, the proportion of C8:0, C10:0, C14:1 cis-9, C16:1 cis-9, and C18:1 cis-9 at sn-2 was positively correlated with the amount of C16:0 in the triacylglycerol; in contrast, saturated C14:0, C16:0, and long-chain saturated FA (C14:0-C18:0) were negatively correlated. These observations suggest that the amount of long-chain saturated FA in TAG influences the positioning of other FA in the TAG. With an interpositional approach, the DGAT1 polymorphism had a significant effect on the proportional positioning of C16:0 at sn-2. These results provide a new direction to controlling functional and compositional differences between milk fats.

The influence of incubation on the formation of volatile bacterial metabolites in mastitis milk

The possibility to detect mastitis-causing pathogens based on their volatile metabolites was previously studied. In that study, the mastitis samples were incubated overnight. To minimize the total analysis time, no incubation, or a short incubation, would be preferred. We therefore investigated the effect of the incubation time on the formation of volatile metabolites in mastitis samples. A selection of 6 volatile metabolites with the highest impact on the prediction model for identifying the mastitis-causing pathogen, was compared at different incubation times between 0 and 24 h. Identification of the pathogens was not possible without incubation. The minimum incubation time for detection of most of the 6 metabolites was 4 to 8 h. Although a longer incubation time increased the differences between pathogens, after 8 h all metabolites could be detected and the pathogens could be differentiated. Eight hours was therefore selected as the optimal incubation time. This optimal incubation time was evaluated with a set of 25 mastitis samples, of which 88% were correctly classified after 8 h of incubation. The total analysis time for this method is therefore considerably shorter than current microbiological culturing.

How NaCl and water content determine water activity during ripening of Gouda cheese, and the predicted effect on inhibition of Listeria monocytogenes.

This study describes the diffusion of NaCl and water in Gouda cheese during brining and ripening. Furthermore, we established water activity as a function of the NaCl-in-moisture content in Gouda cheese during ripening. We determined NaCl content, water content, and water activity in block-type Gouda cheeses that were brined for 3.8d and foil-ripened for a period of 26 wk, and in wheel-type Gouda cheeses that were brined for 0.33, 2.1, or 8.9d and subsequently nature-ripened for a period of 26 wk. The calculated diffusion coefficients of NaCl during brining were 3.6·10(-10) m(2)s(-1) in the block-type Gouda cheeses and 3.5·10(-10) m(2)s(-1) in the wheel-type Gouda cheeses. Immediately after brining, gradients of NaCl and water were observed throughout both types of cheese. During ripening, these gradients disappeared, except for the water gradient in nature-ripened cheeses. An empirical model was derived for Gouda cheese, in which water activity is expressed as a function of the NaCl-in-moisture content, as established for different brining times, locations and ripening times. Moreover, the effect of reduced water activity on inhibition of growth of Listeria monocytogenes in Gouda cheese was calculated. In addition to the presence of lactate and a pH of 5.2 to 5.3, the reduced water activity as seen in Gouda cheese can substantially contribute to inhibition of microbial growth and even to inactivation when cheeses are brined and ripened for extended times and subjected to nature-ripening.

Foam and thin films of hydrophilic silica particles modified by β-casein

HYPOTHESIS Foaming properties of particle dispersions can be modified by addition of amphiphiles. The molar ratio between particles and amphiphiles will influence the wetting properties of the particles as well as the bulk concentration of the amphiphiles. This will have an effect on air/water interfacial composition as well as on the thin film and foam stability of the mixed system. EXPERIMENTS In this research foams and thin films of hydrophilic silica particles in presence of β-casein (β-CN) were investigated with different particle sizes and varying β-CN/silica weight ratios (between 1:10 and 1:100). Samples were characterized for particles size, morphology as well as contact angle and related to their foaming, interfacial, and thin film properties. FINDINGS A threshold weight ratio of β-CN/silica was found to be 1:50 for foam stabilization with mixtures containing silica particles no larger than 1 μm and 1:30 for film stabilization with mixtures containing larger particles. At the interface, the modified silica particles were rather diluted without much interaction for surface compressions up to 30%. Large silica particles (0.0015% β-CN, Csilica ≤ 0.15%) were dragged to the periphery of the thin liquid films but no decrease of the inner film draining rate by a decrease of capilary pressure gradient across the film was observed. The depletion of β-casein in the bulk by particles played a major role in foam destabilization.