Proteolytic activity and heat resistance of the protease AprX from Pseudomonas in relation to genotypic characteristics.

AprX is an alkaline metalloprotease produced by Pseudomonas spp. and encoded by its initial gene of the aprX-lipA operon. The intrinsic diversity among Pseudomonas spp. regarding their proteolytic activity is the main challenge for the development of accurate methods for spoilage prediction of ultra-high temperature (UHT) treated milk in the dairy industry. In the present study, 56 Pseudomonas strains were characterized by assessing their proteolytic activity in milk before and after lab-scale UHT treatment. From these, 24 strains were selected based on their proteolytic activity for whole genome sequencing (WGS) to identify common genotypic characteristics that correlated with the observed variations in proteolytic activity. Four groups (A1, A2, B and N) were determined based on operon aprX-lipA sequence similarities. These alignment groups were observed to significantly influence the proteolytic activity of the strains, with an average proteolytic activity of A1 > A2 > B > N. The lab-scale UHT treatment did not significantly influence their proteolytic activity, indicating a high thermal stability of proteases among strains. Amino acid sequence variation of biologically-relevant motifs in the AprX sequence, namely the Zn2+-binding motif at the catalytic domain and the C-terminal type I secretion signaling mechanism, were found to be highly conserved within alignment groups. These motifs could serve as future potential genetic biomarkers for determination of alignment groups and thereby strain spoilage potential.

Effects of genetic variants and sialylation on in vitro digestibility of purified κ-casein.

Milk with different κ-casein (CN) phenotypes has previously been found to influence its gastric digestion rate. Therefore, the aim of the present study is to disentangle contributions of genetic variation and its related sialylation on the in vitro digestion process of κ-CN. Accordingly, κ-CN was purified from milk representing homozygous cows with κ-CN phenotypes AA, BB, or EE and used as substrate molecules in model studies using the INFOGEST 2.0 in vitro static digestion model. Furthermore, the effect of removal of the terminal sialic acids present on the O-linked oligosaccharides of the purified κ-CN A, B, and E protein variants were studied by desialylation enzymatic assays. The κ-CN proteins were purified by reducing anion exchange chromatography with purities of variants A, B, and E of 93.0, 97.1, and 90.0%, respectively. Protein degradations of native and desialylated κ-CN isolates in gastric and intestinal phases were investigated by sodium dodecyl sulfate-PAGE, degree of hydrolysis (DH), and liquid chromatography electrospray ionization mass spectrometry. It was shown that after purification, the κ-CN molecules reassembled into multimer states, which then constituted the basis for the digestion studies. As assessed by DH, purified variants A and E were found to exhibit faster in vitro digestion rates in both gastric and intestinal phases compared with variant B. Desialylation increased both gastric and intestinal digestion rates for all variants, as measured by DH. In the gastric phase, desialylation promoted digestion of variant B at a rate comparable with native variants A and E, whereas in the intestinal phase, desialylation of variant B promoted better digestion than native A or E. Taken together, the results confirm that low glycosylation degree of purified κ-CN promotes faster in vitro digestion rates, and that desialylation of the O-linked oligosaccharides further promotes digestion. This finding could be applied to produce dairy products with enhanced digestibility.

Phosphorylation and glycosylation isoforms of bovine κ-casein variant E in homozygous Swedish Red cow milk detected by liquid chromatography-electrospray ionization mass spectrometry.

Variations in the phosphorylation and glycosylation patterns of the common κ-casein (CN) variants A and B have been explored, whereas studies on variant E heterogeneity are scarce. This study reports for the first time the detailed phosphorylation and glycosylation pattern of the κ-CN variant E in comparison with variants A and B. Individual cow milk samples representing κ-CN genotype EE (n = 12) were obtained from Swedish Red cows, and the natural posttranslational modifications of its κ-CN were identified and quantified by liquid chromatography-electrospray mass spectrometry. In total, 12 unique isoform masses of κ-CN variant E were identified. In comparison, AA and BB milk consisted of 14 and 17 unique isoform masses, respectively. The most abundant κ-CN E isoform detected in the EE milk was the monophosphorylated, unglycosylated [1P 0G, ∼70%; where P indicates phosphorylation from single to triple phosphorylation (1-3P), and G indicates glycosylation from single to triple glycosylation (1-3G)] form, followed by diphosphorylated, unglycosylated (2P 0G, ∼12%) form, resembling known patterns from variants A and B. However, a clear distinction was the presence of the rare triphosphorylated, nonglycosylated (3P 0G, ∼0.05%) κ-CN isoform in the EE milk. All isoforms detected in variant E were phosphorylated, giving a phosphorylation degree of 100%. This is comparable with the phosphorylation degree of variants A and B, being also almost 100%, though with very small amounts of nonphosphorylated, glycosylated isoforms detected. The glycosylation degree of variant E was found to be around 17%, a bit higher than observed for variant B (around 14%), and higher than variant A (around 7%). Among glycosylation, the glycan e was the most common type identified for all 3 variants, followed by c/d (straight and branched chain trisaccharides, respectively), and b. In contrast to κ-CN variants A and B, no glycan of type a was found in variant E. Taken together, this study shows that the posttranslational modification pattern of variant E resembles that of known variants to a large extent, but with subtle differences.

Differential in vitro digestion rates in gastric phase of bovine milk with different κ-casein phenotypes.

Casein (CN) micelles will coagulate in the stomach after ingestion, which is similar to the cheesemaking process. Although genetic variants of bovine proteins, especially κ-CN, have been confirmed to influence the coagulation properties of the CN micelle, its influence on milk digestibility has not been revealed yet. This study aimed to investigate how genetic variants, glycosylation degree of κ-CN, and CN micelle size influence digestion rates during in vitro gastrointestinal digestion. Three milk pools, representing κ-CN phenotypes of either AA, BB, or AB composition were prepared from milk of individual Danish Holstein cows representing these different genotypes. In vitro digestion of the 3 milk pools, AA, BB, or AB, was investigated by sodium dodecyl sulfate-PAGE, liquid chromatography-mass spectrometry, and degree of hydrolysis. The results showed that κ-CN AA milk had faster digestion rate in the gastric phase compared with BB and AB milks, whereas only small differences were apparent in the intestinal digestion phase. The results further documented that the milk pools representing κ-CN phenotypes BB and AB had comparable overall glycosylation degrees (50.9% and 50.0%, respectively) and higher than that of the AA milk pool (46.9%). Further, the AA milk pool was associated with larger CN micelles. These differences in CN micelle sizes and glycosylation degrees can be part of underlying explanations for the differential in vitro digestion rates observed between the AA, BB, and AB κ-CN milk pools.

Factors influencing milk osteopontin concentration based on measurements from Danish Holstein cows.

Our objective was to determine the content of the bioactive protein osteopontin (OPN) in bovine milk and identify factors influencing its concentration. OPN is expressed in many tissues and body fluids, with by far the highest concentrations in milk. OPN plays a role in immunological and developmental processes and it has been associated with several milk production traits and lactation persistency in cows. In the present study, we report the development of an enzyme linked immunosorbent assay (ELISA) for measurement of OPN in bovine milk. The method was used to determine the concentration of OPN in milk from 661 individual Danish Holstein cows. The median OPN level was determined to 21.9 mg/l with a pronounced level of individual variation ranging from 0.4 mg/l to 67.8 mg/l. Breeding for increased OPN in cow's milk is of significant interest, however, the heritability of OPN in milk was found to be relatively low, with an estimated value of 0.19 in the current dataset. The variation explained by the herd was also found to be low suggesting that OPN levels are not affected by farm management or feeding. Interestingly, the concentration of OPN was found to increase with days in milk and to decrease with parity.

Quantitative LC-MS/MS analysis of high-value milk proteins in Danish Holstein cows.

High-value milk proteins, which can be obtained by optimized fractionation procedures, are ideal ingredients in many food applications. Thus, a simple and robust analytical method is required for the identification and quantification of these individual milk proteins. Here, we present a liquid chromatography-tandem mass spectrometry (LC-MS/MS) method using multiple reaction monitoring (MRM) to simultaneously detect and measure target peptides of two major milk proteins, α-lactalbumin (α-LA) and ß-casein (ß-CN), in raw milk samples from 662 Danish Holstein cows. The MRM quantification of α-LA and ß-CN was achieved with limit of detection (LOD) of 0.14 and 0.16 g/L, respectively and reproducibility of the assay <15%. By this newly established MRM-based method, the concentration of α-LA and ß-CN in an individual cow's milk ranged from 0.5 to 1.9 (average 1.1) g/L, and from 7.5 to 23.4 (average 15) g/L, respectively. There was no significant effect of parity, whereas significantly increasing concentrations of α-LA and ß-CN were observed through lactation (P < 0.001). This shows a considerable biological variation of these two ingredient milk proteins, providing potential varying outputs of fractionation in the dairy streams.

Influence of desialylation of caseinomacropeptide on the denaturation and aggregation of whey proteins.

The effect of the addition of caseinomacropeptide (CMP) or desialylated CMP on the heat-induced denaturation and aggregation of whey proteins was investigated in the pH range 3 to 7 after heating at 80°C for 30 min. The rate and temperature of denaturation, the extent of aggregation, and the changes in secondary structure of the whey proteins heated in presence of CMP or desialylated CMP were measured. The sialic acid bound to CMP favored the denaturation and aggregation of whey proteins when the whey proteins were oppositely charged to CMP at pH 4. A transition occurred at pH 6, below which the removal of sialic acid enhanced the stabilizing properties of CMP against the denaturation and aggregation of the whey proteins. At pH >6, the interactions between desialylated CMP and the whey proteins led to more extensive denaturation and aggregation. Sialic acid bound to CMP influenced the denaturation and aggregation behavior of whey proteins in a pH-dependent manner, and this should be considered in future studies on the heat stability of such systems containing CMP.

Predictive ability of host genetics and rumen microbiome for subclinical ketosis.

Subclinical metabolic disorders such as ketosis cause substantial economic losses for dairy farmers in addition to the serious welfare issues they pose for dairy cows. Major hurdles in genetic improvement against metabolic disorders such as ketosis include difficulties in large-scale phenotype recording and low heritability of traits. Milk concentrations of ketone bodies, such as acetone and ß-hydroxybutyric acid (BHB), might be useful indicators to select cows for low susceptibility to ketosis. However, heritability estimates reported for milk BHB and acetone in several dairy cattle breeds were low. The rumen microbial community has been reported to play a significant role in host energy homeostasis and metabolic and physiologic adaptations. The current study aims at investigating the effects of cows' genome and rumen microbial composition on concentrations of acetone and BHB in milk, and identifying specific rumen microbial taxa associated with variation in milk acetone and BHB concentrations. We determined the concentrations of acetone and BHB in milk using nuclear magnetic resonance spectroscopy on morning milk samples collected from 277 Danish Holstein cows. Imputed high-density genotype data were available for these cows. Using genomic and microbial prediction models with a 10-fold resampling strategy, we found that rumen microbial composition explains a larger proportion of the variation in milk concentrations of acetone and BHB than do host genetics. Moreover, we identified associations between milk acetone and BHB with some specific bacterial and archaeal operational taxonomic units previously reported to have low to moderate heritability, presenting an opportunity for genetic improvement. However, higher covariation between specific microbial taxa and milk acetone and BHB concentrations might not necessarily indicate a causal relationship; therefore further validation is needed before considering implementation in selection programs.

Realization of breeding values for milk fatty acids in relation to seasonal variation in organic milk.

Prediction of detailed milk fatty acid (FA) composition by mid-infrared spectroscopy (MIRS) offers possibilities for high-throughput indirect measurements of detailed milk compositional parameters through the milk testing system, which can be used to differentiate the FA profile by genetics or specific management or on dairies for milk quality evaluation. Since 2015, milk samples from all Danish dairy cows under milk testing have been recorded using MIRS. The MIRS software from the FOSS Application Note 64 was used to predict contents of 7 FA groups and 4 individual FA. Data generated from the application note have been used to estimate breeding values for sires for percentage of saturated fat (SFA%) in milk. To investigate whether extreme SFA% breeding values of sires were reflected in the detailed milk FA profile from their daughters, milk samples from 194 cows in 7 organic herds were collected and the detailed FA composition measured by gas chromatography. From each cow, milk samples were collected twice to explore specific seasonal effects of pasture-based diets in relation to sires' estimated breeding value (EBV) for MIRS-predicted SFA% (MIRS-SFA%). The results showed a significant difference in SFA% measured from GC (GC-SFA%) in milk from daughters of sires having high SFA% EBV compared with daughters of sires having low SFA% EBV. The EBV group (low or high) also significantly affected most FA except C13:0, C15:0, C17:0, and C18:1 trans-11. Contents of SFA with even chain-lengths were all higher in the high EBV group, whereas C14:1, C16:1, and the other unsaturated C18 FA had a higher content in the low EBV group. All FA were significantly affected by season. The SFA% decreased from indoor spring feeding to summer pasture, as did FA with chain length ≤16 carbons, whereas long-chain FA (>C17) all increased during summer pasture. The results show that use of MIRS-predicted EBV for SFA% will most likely display a correlated response on the detailed FA composition in milk. In the current study, the combined action of feeding and genetics resulted in a 10 percentage-point difference on average when comparing milk SFA% from daughters of high SFA% EBV sires during indoor spring feeding from one farm to milk SFA% from daughters of low SFA% EBV sires during summer from another farm.

Impact of the rumen microbiome on milk fatty acid composition of Holstein cattle.

BACKGROUND: Fatty acids (FA) in bovine milk derive through body mobilization, de novo synthesis or from the feed via the blood stream. To be able to digest feedstuff, the cow depends on its rumen microbiome. The relative abundance of the microbes has been shown to differ between cows. To date, there is little information on the impact of the microbiome on the formation of specific milk FA. Therefore, in this study, our aim was to investigate the impact of the rumen bacterial microbiome on milk FA composition. Furthermore, we evaluated the predictive value of the rumen microbiome and the host genetics on the composition of individual FA in milk. RESULTS: Our results show that the proportion of variance explained by the rumen bacteria composition (termed microbiability or [Formula: see text]) was generally smaller than that of the genetic component (heritability), and that rumen bacteria influenced most C15:0, C17:0, C18:2 n-6, C18:3 n-3 and CLA cis-9, trans-11 with estimated [Formula: see text] ranging from 0.26 to 0.42. For C6:0, C8:0, C10:0, C12:0, C16:0, C16:1 cis-9 and C18:1 cis-9, the variance explained by the rumen bacteria component was close to 0. In general, both the rumen microbiome and the host genetics had little value for predicting FA phenotype. Compared to genetic information only, adding rumen bacteria information resulted in a significant improvement of the predictive value for C15:0 from 0.22 to 0.38 (P = 9.50e-07) and C18:3 n-3 from 0 to 0.29 (P = 8.81e-18). CONCLUSIONS: The rumen microbiome has a pronounced influence on the content of odd chain FA and polyunsaturated C18 FA, and to a lesser extent, on the content of the short- and medium-chain FA in the milk of Holstein cattle. The accuracy of prediction of FA phenotypes in milk based on information from either the animal's genotypes or rumen bacteria composition was very low.

A genome-wide association study reveals specific transferases as candidate loci for bovine milk oligosaccharides synthesis.

BACKGROUND: Human milk oligosaccharides (OS) play a key role in brain and gut microbiota development of the neonate, but the underlying biosynthetic steps of OS in the mammary gland are still largely unknown. As bovine milk contains OS with somewhat similar structures and functionalities there is increased interest in further understanding the genetic basis underlying the OS content of milk for eventual extraction and generation of value-added ingredients for infant formulas and nutraceuticals. The present study is the first to report on genetic parameter estimation as well as on a genome wide association study (GWAS) from the largest bovine milk OS dataset analyzed to date. RESULTS: In total 15 different bovine milk OS were monitored. Heritabilities ranged from 0 to 0.68 in Danish Holstein and from 0 to 0.92 in Danish Jersey. The GWAS identified in total 1770 SNPs (FDR < 0.10) for five different OS in Danish Holstein and 6913 SNPs (FDR < 0.10) for 11 OS in Danish Jersey. In Danish Holstein, a major overlapping QTL was identified on BTA1 for LNH and LNT explaining 24% of the variation in these OS. The most significant SNPs were associated with B3GNT5, a gene encoding a glycosyltransferase involved in glycan synthesis. In Danish Jersey, a very strong QTL was detected for the OS with composition 2 Hex 1 HexNAc (isomer 1) on BTA11. The most significant SNP had -log10(P-value) of 52.88 (BOVINEHD1100030300) and was assigned to ABO, a gene encoding ABO blood group glycosyltransferases. This SNP has been reported to be a missense mutation and explains 56% of the OS variation. Other candidate genes of interest identified for milk OS were ALG3, B3GALNT2, LOC520336, PIGV, MAN1C1, ST6GALNAC6, GLT6D1, GALNT14, GALNT17, COLGALT2, LFNG and SIGLEC. CONCLUSION: To our knowledge, this is the first study documenting a solid breeding potential for bovine milk OS and a strong indication of specific candidate genes related to OS synthesis underlying this genetic influence. This new information has the potential to guide breeding strategies to achieve production of milk with higher diversity and concentration of OS and ultimately facilitate large-scale extraction of bovine milk OS.

Reliability of genomic prediction for milk fatty acid composition by using a multi-population reference and incorporating GWAS results.

BACKGROUND: Large-scale phenotyping for detailed milk fatty acid (FA) composition is difficult due to expensive and time-consuming analytical techniques. Reliability of genomic prediction is often low for traits that are expensive/difficult to measure and for breeds with a small reference population size. An effective method to increase reference population size could be to combine datasets from different populations. Prediction models might also benefit from incorporation of information on the biological underpinnings of quantitative traits. Genome-wide association studies (GWAS) show that genomic regions on Bos taurus chromosomes (BTA) 14, 19 and 26 underlie substantial proportions of the genetic variation in milk FA traits. Genomic prediction models that incorporate such results could enable improved prediction accuracy in spite of limited reference population sizes. In this study, we combine gas chromatography quantified FA samples from the Chinese, Danish and Dutch Holstein populations and implement a genomic feature best linear unbiased prediction (GFBLUP) model that incorporates variants on BTA14, 19 and 26 as genomic features for which random genetic effects are estimated separately. Prediction reliabilities were compared to those estimated with traditional GBLUP models. RESULTS: Predictions using a multi-population reference and a traditional GBLUP model resulted in average gains in prediction reliability of 10% points in the Dutch, 8% points in the Danish and 1% point in the Chinese populations compared to predictions based on population-specific references. Compared to the traditional GBLUP, implementation of the GFBLUP model with a multi-population reference led to further increases in prediction reliability of up to 38% points in the Dutch, 23% points in the Danish and 13% points in the Chinese populations. Prediction reliabilities from the GFBLUP model were moderate to high across the FA traits analyzed. CONCLUSIONS: Our study shows that it is possible to predict genetic merits for milk FA traits with reasonable accuracy by combining related populations of a breed and using models that incorporate GWAS results. Our findings indicate that international collaborations that facilitate access to multi-population datasets could be highly beneficial to the implementation of genomic selection for detailed milk composition traits.

Profiling of aminoxyTMT-labeled bovine milk oligosaccharides reveals substantial variation in oligosaccharide abundance between dairy cattle breeds.

Free milk oligosaccharides are bioactive molecules that function as prebiotics and prevent infections that commonly afflict developing infants. To date, few publications have examined the factors affecting bovine milk oligosaccharide production among cattle in the dairy industry. Here we have applied a high-throughput isobaric labeling technique to measure oligosaccharide abundances in milk collected from Danish Holstein-Friesian and Jersey dairy cattle by liquid chromatography-mass spectrometry. With a total of 634 milk samples, this collection represents the largest sample set used for milk oligosaccharide profiling in the current literature. This study is also the first to use isobaric labeling for the purpose of measuring free oligosaccharides in a real sample set. We have identified 13 oligosaccharides that vary significantly by breed, with most structures being more abundant in the milk of Jersey cattle. The abundances of several oligosaccharides were increased in second-parity cows, and correlations between the abundances of oligosaccharide pairs were identified, potentially indicating similarities in their synthetic pathways. Fucosylated oligosaccharide structures were widely identified among both breeds. Improving our understanding of oligosaccharide production will aid in developing strategies to recover these compounds from processing streams and may enable their use as a functional ingredient in foods for infants and adults.

An improved method for the purification of milk oligosaccharides by graphitised carbon-solid phase extraction.

Milk oligosaccharides (OS) are bioactive molecules that impart a variety of health benefits to the consumer. Techniques commonly used to analyse and quantify OS require optimised extraction methods to separate the OS from more abundant milk components. Solid phase extraction (SPE) is frequently used to isolate milk OS from lactose; however, the literature contains no formal studies on its efficacy in this application. In this study, established SPE conditions were modified to improve the technique's effectiveness in purifying OS from lactose. Low concentrations of acetonitrile (ACN) and trifluoroacetic acid (TFA) were tested for solid phase washing. Lactose removal and retention of many OS were significantly improved when using 4% ACN/0.1% TFA compared with the more common water washing technique. Different behaviours between acidic and neutral OS were evident. The new SPE technique improves extraction efficiency for bovine milk OS in applications that do not require prior lactose hydrolysis.

Modeling heterogeneous (co)variances from adjacent-SNP groups improves genomic prediction for milk protein composition traits.

BACKGROUND: Accurate genomic prediction requires a large reference population, which is problematic for traits that are expensive to measure. Traits related to milk protein composition are not routinely recorded due to costly procedures and are considered to be controlled by a few quantitative trait loci of large effect. The amount of variation explained may vary between regions leading to heterogeneous (co)variance patterns across the genome. Genomic prediction models that can efficiently take such heterogeneity of (co)variances into account can result in improved prediction reliability. In this study, we developed and implemented novel univariate and bivariate Bayesian prediction models, based on estimates of heterogeneous (co)variances for genome segments (BayesAS). Available data consisted of milk protein composition traits measured on cows and de-regressed proofs of total protein yield derived for bulls. Single-nucleotide polymorphisms (SNPs), from 50K SNP arrays, were grouped into non-overlapping genome segments. A segment was defined as one SNP, or a group of 50, 100, or 200 adjacent SNPs, or one chromosome, or the whole genome. Traditional univariate and bivariate genomic best linear unbiased prediction (GBLUP) models were also run for comparison. Reliabilities were calculated through a resampling strategy and using deterministic formula. RESULTS: BayesAS models improved prediction reliability for most of the traits compared to GBLUP models and this gain depended on segment size and genetic architecture of the traits. The gain in prediction reliability was especially marked for the protein composition traits ß-CN, κ-CN and ß-LG, for which prediction reliabilities were improved by 49 percentage points on average using the MT-BayesAS model with a 100-SNP segment size compared to the bivariate GBLUP. Prediction reliabilities were highest with the BayesAS model that uses a 100-SNP segment size. The bivariate versions of our BayesAS models resulted in extra gains of up to 6% in prediction reliability compared to the univariate versions. CONCLUSIONS: Substantial improvement in prediction reliability was possible for most of the traits related to milk protein composition using our novel BayesAS models. Grouping adjacent SNPs into segments provided enhanced information to estimate parameters and allowing the segments to have different (co)variances helped disentangle heterogeneous (co)variances across the genome.

Comparison of milk protein composition and rennet coagulation properties in native Swedish dairy cow breeds and high-yielding Swedish Red cows.

Recent studies have reported a very high frequency of noncoagulating milk in Swedish Red cows. The underlying factors are not fully understood. In this study, we explored rennet-induced coagulation properties and relative protein profiles in milk from native Swedish Mountain and Swedish Red Polled cows and compared them with a subset of noncoagulating (NC) and well-coagulating (WC) milk samples from modern Swedish Red cows. The native breeds displayed a very low prevalence of NC milk and superior milk coagulation properties compared with Swedish Red cows. The predominant variants in both native breeds were αS1-casein (αS1-CN) B, ß-CN A2 and ß-lactoglobulin (ß-LG) B. For κ-CN, the B variant was predominant in the Swedish Mountain cows, whereas the A variant was the most frequent in the Swedish Red Polled. The native breeds displayed similar protein composition, but varied in content of αS1-CN with 9 phosphorylated serines (9P) form. Within the Swedish Mountain cows, we observed a strong inverse correlation between the relative concentration of κ-CN and micelle size and a positive correlation between ionic calcium and gel firmness. For comparison, we investigated a subset of 29 NC and 28 WC milk samples, representing the extremes with regard to coagulation properties based on an initial screening of 395 Swedish Red cows. In Swedish Red, NC milk properties were found to be related to higher frequencies of ß-CN A2, κ-CN E and A variants, as well as ß-LG B, and the predominant composite genotype of ß- and κ-CN in the NC group was A2A2/AA. Generally, the A2A2/AA composite genotype was related to lower relative concentrations of κ-CN isoforms and higher relative concentrations of αS1-, αS2-, and ß-CN. Compared with the group of WC milk samples, NC milk contained a higher fraction of αS2-CN and α-lactalbumin (α-LA) but a lower fraction of αS1-CN 9P. In conclusion, milk from native Swedish breeds has good characteristics for cheese milk, which could be exploited in niche dairy products. In milk from Swedish Mountain cows, levels of ionic calcium seemed to be more important for rennet-induced gel firmness than variation in the relative protein profile. In Swedish Red, lower protein content as well as higher fraction of αS2-CN and lower fraction of αS1-CN 9P were related to NC milk. Further, a decrease in the frequency of the composite ß-κ-CN genotype A2A2/AA through selective breeding could have a positive effect on milk coagulation properties.

Estimation of genetic parameters and detection of chromosomal regions affecting the major milk proteins and their post translational modifications in Danish Holstein and Danish Jersey cattle.

BACKGROUND: In the Western world bovine milk products are an important protein source in human diet. The major proteins in bovine milk are the four caseins (CN), αS1-, αS2-, ß-, and k-CN and the two whey proteins, ß-LG and α-LA. It has been shown that both the amount of specific CN and their isoforms including post-translational modifications (PTM) influence technological properties of milk. Therefore, the aim of this study was to 1) estimate genetic parameters for individual proteins in Danish Holstein (DH) (n = 371) and Danish Jersey (DJ) (n = 321) milk, and 2) detect genomic regions associated with specific milk protein and their different PTM forms using a genome-wide association study (GWAS) approach. RESULTS: For DH, high heritability estimates were found for protein percentage (0.47), casein percentage (0.43), k-CN (0.77), ß-LG (0.58), and α-LA (0.40). For DJ, high heritability estimates were found for protein percentage (0.70), casein percentage (0.52), and α-LA (0.44). The heritability for G-k-CN, U-k-CN and GD was higher in the DH compared to the DJ, whereas the heritability for the PD of αS1-CN was lower in DH compared to DJ, whereas the PD for αS2-CN was higher in DH compared to DJ. The GWAS results for the main milk proteins were in line what has been earlier published. However, we showed that there were SNPs specifically regulating G-k-CN in DH. Some of these SNPs were assigned to casein protein kinase genes (CSNK1G3, PRKCQ). CONCLUSION: The genetic analysis of the major milk proteins and their PTM forms revealed that these were heritable in both DH and DJ. In DH, genomic regions specific for glycosylation of k-CN were detected. Furthermore, genomic regions for the major milk proteins confirmed the regions on BTA6 (casein cluster), BTA11 (PEAP), and BTA14 (DGAT1) as important regions influencing protein composition in milk. The results from this study provide confidence that it is possible to breed for specific milk protein including the different PTM forms.

Estimation of genetic parameters and detection of quantitative trait loci for minerals in Danish Holstein and Danish Jersey milk.

BACKGROUND: Bovine milk provides important minerals, essential for human nutrition and dairy product quality. For changing the mineral composition of the milk to improve dietary needs in human nutrition and technological properties of milk, a thorough understanding of the genetics underlying milk mineral contents is important. Therefore the aim of this study was to 1) estimate the genetic parameters for individual minerals in Danish Holstein (DH) (n=371) and Danish Jersey (DJ) (n=321) milk, and 2) detect genomic regions associated with mineral content in the milk using a genome-wide association study (GWAS) approach. RESULTS: For DH, high heritabilities were found for Ca (0.72), Zn (0.49), and P (0.46), while for DJ, high heritabilities were found for Ca (0.63), Zn (0.57), and Mg (0.57). Furthermore, intermediate heritabilities were found for Cu in DH, and for K, Na, P and Se in the DJ. The GWAS revealed a total of 649 significant SNP markers detected for Ca (24), Cu (90), Fe (111), Mn (3), Na (1), P (4), Se (12) and Zn (404) in DH, while for DJ, a total of 787 significant SNP markers were detected for Ca (44), Fe (43), K (498), Na (4), Mg (1), P (94) and Zn (3). Comparing the list of significant markers between DH and DJ revealed that the SNP ARS-BFGL-NGS-4939 was common in both breeds for Zn. This SNP marker is closely linked to the DGAT1 gene. Even though we found significant SNP markers on BTA14 in both DH and DJ for Ca, and Fe these significant SNPs did not overlap. CONCLUSION: The results show that Ca, Zn, P and Mg show high heritabilities. In combination with the GWAS results this opens up possibilities to select for specific minerals in bovine milk.

Short communication: Genetic variation of riboflavin content in bovine milk.

Riboflavin (vitamin B2) is an essential water-soluble vitamin; elderly people and adolescents in particular can have poor riboflavin status. In Western diets, milk and dairy products are primary sources of riboflavin, but little is known about the natural variation within and among bovine breeds, and how genetic and environmental factors can affect the riboflavin content in milk. As a part of the Danish-Swedish Milk Genomics Initiative, the aim of the study was to quantify milk riboflavin content using reverse-phase HPLC in 2 major Danish dairy breeds. The results showed substantial interbreed differences in milk riboflavin content. Milk from Danish Jersey cows contained significantly higher levels of riboflavin (1.93mg/L of milk) than milk from Danish Holstein cows (1.40mg/L of milk). Furthermore, genetic analyses revealed high heritabilities in both breeds (0.52 for Danish Holstein and 0.31 for Danish Jersey). A genomic association study found 35 significant single nucleotide polymorphisms (false discovery rate<0.10) to be associated with riboflavin content in milk in Jersey cows (all on BTA14 and BTA17), and 511 significant single nucleotide polymorphisms in Holstein cows spread over 25 different autosomes with BTA13 and BTA14 having the most promising quantitative trait loci. The best candidate gene found within the identified quantitative trait loci was SLC52A3, a riboflavin transporter gene, which was among the significant markers on BTA13 in Holstein cows.

Genetic variation and posttranslational modification of bovine κ-casein: effects on caseino-macropeptide release during renneting.

Chymosin-induced cleavage of κ-casein (κ-CN) occurs during the first enzymatic phase in milk coagulation during cheese manufacturing, where the hydrophilic C-terminal peptide of κ-CN, named caseino-macropeptide (CMP), is released into the whey. The CMP peptide is known for its rather heterogeneous composition with respect to both genetic variation and multiple posttranslational modifications, including phosphorylation and O-linked glycosylation. An approach of liquid chromatography coupled with mass spectrometry was used to investigate (1) the overall protein profile and (2) the release of various forms of CMP after addition of chymosin to individual cow milk samples from 2 breeds, Danish Jersey (DJ) and Danish Holstein-Friesian (DH). The cows were selected to represent distinct homo- and heterozygous types of the κ-CN genetic variants A, B, and E (i.e., genotypes AA, BB, AB, EE, and AE). Initially, investigation of the protein profile showed milk with κ-CN BB exhibited the highest relative content of κ-CN, whereas AE milk exhibited the lowest, and after 40min of renneting >90% of intact κ-CN was hydrolyzed by chymosin in milk representing all κ-CN genotype. By in-depth analysis of the CMP chromatographic profile, multiple CMP isoforms with 1 to 3 O-linked glycans (1-3 G) and 1 to 3 phosphate groups (1-3 P) were identified, as well as nonmodified CMP isoforms. The number of identified CMP isoforms varied to some extent between breeds (21CMP isoforms identified in DJ, 26CMP isoforms in DH) and between κ-CN genetic variants (CMP variant A being the most heterogeneous compared with CMP B and E), as well as between individual samples within each breed. The predominant forms of glycans attached to CMP were found to be the acidic tetrasaccharide {N-acetyl-neuraminic acid α(2-3)galactose ß(1-3)[N-acetyl-neuraminic acid α(2-6)]N-acetyl galactose} or trisaccharides {N-acetyl-neuraminic acid α(2-3)galactose ß(1-3)N-acetyl galactose and galactose ß(1-3)[N-acetyl-neuraminic acid (α2-6)]N-acetyl galactose}. The CMP release was calculated to follow first-order kinetics and was determined by the measurement of CMP content during renneting. The highest rate of release for all CMP isoforms occurred from 0 to 2min after chymosin addition. Concurring results from both breeds showed that CMP variant A with 1-2 P had the highest reaction rate of CMP release, followed by CMP B 1-2 P and then by CMP E 1-2 P (only in DH). All the identified glycosylated CMP isoforms had lower reaction rates of release compared with that of nonglycosylated CMP, thus glycan modifications seemed to negatively influence the reaction rate of chymosin-induced hydrolysis of κ-CN.