Solubility of commercial milk protein concentrates and milk protein isolates

High-protein milk protein concentrate (MPC) and milk protein isolate (MPI) powders may have lower solubility than low-protein MPC powders, but information is limited on MPC solubility. Our objectives in this study were to (1) characterize the solubility of commercially available powder types with differing protein contents such as MPC40, MPC80, and MPI obtained from various manufacturers (sources), and (2) determine if such differences could be associated with differences in mineral, protein composition, and conformational changes of the powders. To examine possible predictors of solubility as measured by percent suspension stability (%SS), mineral analysis, Fourier transform infrared (FTIR) spectroscopy, and quantitative protein analysis by HPLC was performed. After accounting for overall differences between powder types, %SS was found to be strongly associated with the calcium, magnesium, phosphorus, and sodium content of the powders. The FTIR score plots were in agreement with %SS results. A principal component analysis of FTIR spectra clustered the highly soluble MPC40 separately from the rest of samples. Furthermore, 2 highly soluble MPI samples were clustered separately from the rest of the MPC80 and MPI samples. We found that the 900 to 1,200 cm⁻¹ region exhibited the highest discriminating power, with dominant bands at 1,173 and 968 cm⁻¹, associated with phosphate vibrations. The 2 highly soluble MPI powders were observed to have lower κ-casein and α-_S1-casein contents and slightly higher whey protein contents than the other powders. The differences in the solubility of MPC and MPI were associated with a difference in mineral composition, which may be attributed to differences in processing conditions. Additional studies on the role of minerals composition on MPC80 solubility are warranted. Such a study would provide a greater understanding of factors associated with differences in solubility and can provide insight on methods to improve solubility of high-protein milk protein concentrates.     

Impact of somatic cell count combined with differential somatic cell count on milk protein fractions in Holstein cattle

Udder health in dairy herds is a very important issue given its implications for animal welfare and the production of high-quality milk. Somatic cell count (SCC) is the most widely used means of assessing udder health status. However, differential somatic cell count (DSCC) has recently been proposed as a new and more effective means of evaluating intramammary infection dynamics. Differential SCC represents the combined percentage of polymorphonuclear neutrophils and lymphocytes (PMN-LYM) in the total SCC, with macrophages (MAC) accounting for the remaining proportion. The aim of this study was to evaluate the association between SCC and DSCC and the detailed milk protein profile in a population of 1,482 Holstein cows. A validated reversed-phase HPLC method was used to quantify 4 caseins (CN), namely α_S1-CN, α_S2-CN, κ-CN, and β-CN, and 3 whey protein fractions, namely β-lactoglobulin, α-lactalbumin, and lactoferrin, which were expressed both quantitatively (g/L) and qualitatively (as a percentage of the total milk nitrogen content, %N). A linear mixed model was fitted to explore the associations between somatic cell score (SCS) combined with DSCC and the protein fractions expressed quantitatively and qualitatively. We ran an additional model that included DSCC expressed as PMN-LYM and MAC counts, obtained by multiplying the percentages of PMN-LYM and MAC by SCC for each cow in the data set. When the protein fractions were expressed as grams per liter, SCS was significantly negatively associated with almost all the casein fractions and positively associated with the whey protein α-lactalbumin, while DSCC was significantly associated with α_S1-CN, β-CN, and α-lactalbumin, but in the opposite direction to SCS. We observed the same pattern with the qualitative data (i.e., %N), confirming opposite effects of SCS and DSCC on milk protein fractions. The PMN-LYM count was only slightly associated with the traits of concern, although the pattern observed was the same as when both SCS and DSCC were included in the model. The MAC count, however, generally had a greater impact on many casein fractions, in particular decreasing both β-CN content (g/L) and proportion (%N), and exhibited the opposite pattern to the PMN-LYM count. Our results show that information obtained from both SCS and DSCC may be useful in assessing milk quality and protein fractions. They also demonstrate the potential of MAC count as a novel udder health trait.     

Protein interactions in milk protein concentrate powders

Solutions (5%, w/w, pH 6.9), made from six different pilot-plant milk protein concentrate (MPC) powders, were centrifuged (700 g for 10 min at 20 °C) to isolate the insoluble material. The sediment (insoluble material) was characterized using one-dimensional (1D) and two-dimensional (2D) sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS-PAGE) and transmission electron microscopy (TEM). The levels of solubility in MPC powders varied between 32% and 98%. The TEM results showed that the insoluble material consisted of large particles (∼100 μm) where the casein micelles are fused together by some form of protein–protein interactions. The 1D PAGE results showed that the amounts of insoluble material in MPC powders increased with storage time at elevated temperatures. This material consisted predominantly of α- and β-caseins. This material was formed largely by weak non-covalent (hydrophobic) protein–protein interactions that were dissociable under SDS-PAGE conditions. The 2D PAGE results demonstrated that the disulphide-linked protein aggregates present in MPC powders consisted of κ-casein, β-lactoglobulin and some α_s2-casein, and not all of this material was sedimented. These aggregates were not considered to play a major role in the formation of the insoluble material.     

Genetic analysis of detailed milk protein composition and coagulation properties in Simmental cattle

The objective of this study was to estimate genetic parameters for milk protein fraction contents, milk protein composition, and milk coagulation properties (MCP). Contents of α_S1-, α_S2-, β-, γ-, and κ-casein (CN), β-lactoglobulin (β-LG), and α-lactalbumin (α-LA) were measured by reversed-phase HPLC in individual milk samples of 2,167 Simmental cows. Milk protein composition was measured as percentage of each CN fraction in CN (α_S1-CN%, α_S2-CN%, β-CN%, γ-CN%, and κ-CN%) and as percentage of β-LG in whey protein (β-LG%). Rennet clotting time (RCT) and curd firmness (a₃₀) were measured by a computerized renneting meter. Heritabilities for contents of milk proteins ranged from 0.11 (α-LA) to 0.52 (κ-CN). Heritabilities for α_S1-CN%, κ-CN%, and β-CN% were similar and ranged from 0.63 to 0.69, whereas heritability of α_S2-CN%, γ-CN%, and β-LG% were 0.28, 0.18, and 0.34, respectively. Effects of CSN2-CSN3 haplotype and BLG genotype accounted for more than 80% of the genetic variance of α_S1-CN%, β-CN%, and κ-CN% and 50% of the genetic variance of β-LG%. The genetic correlations among the contents of CN fractions and between CN and whey protein fractions contents were generally low. When the data were adjusted for milk protein gene effects, the magnitude of the genetic correlations among the contents of milk protein fractions markedly increased, indicating that they undergo a common regulation. The proportion of β-CN in CN correlated negatively with κ-CN% (r = −0.44). The genetic relationships between CN and whey protein composition were trivial. Low milk pH correlated with favorable MCP. Genetically, contents and proportions of α_S1- and α_S2-CN in CN were positively correlated with RCT. The relative proportion of β-CN in CN exhibited a genetic correlation with RCT of −0.26. Both the content and the relative proportion of κ-CN in CN did not correlate with RCT. Weak curds were genetically associated with increased proportions in CN of α_S1- and α_S2-CN, decreased contents of β-CN and κ-CN, and decreased proportion of κ-CN in CN. Negligible effects on the estimated correlations between a₃₀ and κ-CN contents or proportion in CN were observed when the model accounted for milk protein gene effects. Increasing β-CN and κ-CN contents and relative proportions in CN and decreasing the content and proportions of α_S1-CN and α_S2-CN and milk pH through selective breeding exert favorable effects on MCP.     

挤压温度对挤压大米蛋白与葡萄糖复合物功能和结构特性的影响

为获得一种快速、有效的工业化生产方法,本研究在大米蛋白与葡萄糖发生美拉德反应前对大米蛋白进行挤压改性。大米蛋白在不同温度（80、90、100、110、120、130 ℃）下挤压,然后在pH 10.5条件下与葡萄糖接合30 min。分析不同挤压温度对其功能性质（溶解度、乳化活性和乳化稳定性）的影响,利用扫描电子显微镜、傅里叶变换红外光谱和十二烷基硫酸钠-聚丙稀酰胺凝胶电泳对挤压后的大米蛋白和葡萄糖复合物进行结构表征。结果表明：与天然大米蛋白质和葡萄糖（native rice protein and glucose,NRPG）复合物相比,挤压大米蛋白和葡萄糖（extruded rice protein and glucose,ERPG）复合物在90 ℃的糖基化程度最高。与NRPG相比,ERPG（90～120 ℃）的溶解度降低,ERPG（80～90 ℃）的乳化活性、乳化稳定性和表面疏水性升高,而100～130 ℃的时候缓慢降低。红外光谱结果表明,与NRPG相比,ERPG具有较高的α-螺旋、β-转角和无规卷曲,β-折叠结构相对含量较低。十二烷基硫酸钠-聚丙稀酰胺凝胶电泳显示蛋白质通过挤压聚合成更大的颗粒。扫描电子显微镜显示,ERPG具有更多的无序结构和不规则碎片。     

Edam牦牛干酪成熟过程中品质变化及蛋白质降解

为研究Edam牦牛半硬质干酪成熟机理，分别测定成熟0、20、40、60、80 d Edam牦牛干酪的感官、理化、物性、蛋白质和脂肪分解指标，采用十二烷基硫酸钠-聚丙烯酰胺凝胶电泳和傅里叶变换红外光谱等方法研究酪蛋白降解情况，通过Pearson相关性分析成熟时间与各指标间的相关性。结果表明：随着成熟时间延长，感官评分先下降后上升；水分含量、pH值下降；亮度值（L*）下降，红度值（a*）和黄度值（b*）值上升；硬度、弹性、胶黏性均上升，凝聚性逐渐下降；储能模量和损耗模量升高，损耗角正切值始终小于1；成熟时间与总氮含量、pH 4.6和12%三氯乙酸条件下干酪中可溶性氮含量等呈极显著正相关（P<0.01）；脂肪含量先升高后降低，游离脂肪酸含量和硫代巴比妥酸值逐渐增加。酪蛋白（casein,CN）降解研究结果表明：αs1-CN、αs2-CN、β-CN及κ-CN均随成熟时间延长而不断降解，成熟80 d时大分子蛋白降解明显；成熟过程中β-折叠、α-螺旋逐渐向无规卷曲转化；成熟时间与羰基含量、表面疏水性呈极显著正相关（P<0.01），与总巯基含量呈显著负相关（P<0.05）。     

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

The effects of β-lactoglobulin (β-LG), β-casein (β-CN), and κ-CN variants and β-κ-CN haplotypes on the relative concentrations of the major milk proteins α-lactalbumin (α-LA), β-LG, α_S1-CN, α_S2-CN, β-CN, and κ-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 β-LG genotype was associated with the relative concentrations of β-LG (A » B) and of α-LA, α_S1-CN, α_S2-CN, β-CN, and κ-CN (B > A) but not with any milk production trait. The β-CN genotype was associated with the relative concentrations of β-CN and α_S2-CN (A² > A¹) and of α_S1-CN and κ-CN (A¹ > A²) and with protein yield (A² > A¹). The κ-CN genotype was associated with the relative concentrations of κ-CN (B > E > A), α_S2-CN (B > A), α-LA, and α_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 β-LG genotype B and the β-κ-CN haplotype A²B will result in cows that produce milk that is more suitable for cheese production.     

Ageing-induced solubility loss in milk protein concentrate powder: effect of protein conformational modifications and interactions with water

BACKGROUND: Protein conformational modifications and water‐protein interactions are two major factors believed to induce instability of protein and eventually affect the solubility of milk protein concentrate (MPC) powder. To test these hypotheses, MPC was stored at different water activities (a_w 0.0–0.85) and temperatures (25 and 45 °C) for up to 12 weeks. Samples were examined periodically to determine solubility, change in protein conformation by Fourier transform infrared (FTIR) spectroscopy and water status (interaction of water with the protein molecule/surface) by measuring the transverse relaxation time (T₂) with proton nuclear magnetic resonance (¹H NMR). RESULTS: The solubility of MPC decreased significantly with ageing and this process was enhanced by increasing water activity (a_w) and temperature. Minor changes in protein secondary structure were observed with FTIR which indicated some degree of unfolding of protein molecules. The NMR T₂ results indicated the presence of three distinct populations of water molecules and the proton signal intensity and T₂ values of proton fractions varied with storage condition (humidity) and ageing. CONCLUSION: Results suggest that protein/protein interactions may be initiated by unfolding of protein molecules that eventually affects solubility. Copyright © 2011 Society of Chemical Industry     

Effect of NaCl addition during diafiltration on the solubility, hydrophobicity, and disulfide bonds of 80% milk protein concentrate powder

We investigated the surface hydrophobicity index based on different fluorescence probes [1-anilinonaphthalene-8-sulfonic acid (ANS) and 6-propionyl-2-(N,N-dimethylamino)-naphthalene (PRODAN)], free sulfhydryl and disulfide bond contents, and particle size of 80% milk protein concentrate (MPC80) powders prepared by adding various amounts of NaCl (0, 50, 100, and 150 mM) during the diafiltration process. The solubility of MPC80 powder was not strictly related to surface hydrophobicity. The MPC80 powder obtained by addition of 150 mM NaCl during diafiltration had the highest solubility but also the highest ANS-based surface hydrophobicity, the lowest PRODAN-based surface hydrophobicity, and the least aggregate formation. Intermolecular disulfide bonds caused by sulfhydryl-disulfide interchange reactions and hydrophobic interactions may be responsible for the lower solubility of the control MPC80 powder. The enhanced solubility of MPC80 powder with addition of NaCl during diafiltration may result from the modified surface hydrophobicity, the reduced intermolecular disulfide bonds, and the associated decrease in mean particle size. Addition of NaCl during the diafiltration process can modify the strength of hydrophobic interactions and sulfhydryl-disulfide interchange reactions and thereby affect protein aggregation and the solubility of MPC powders.     

Occurrence of β-casein fragments in cold-stored and curdled river buffalo (Bubalus bubalis L.) milk

The safeguard of river buffalo Mozzarella cheese, a Protected Designation of Origin dairy product, has prompted an analytical study to trace the milk and curd used as raw material in cheesemaking. This is to prevent the illegal use of milk or curd from different geographical areas outside of those indicated in the official production protocol. For this purpose, we studied primary proteolysis occurring in fresh and frozen milk and curd to identify a molecular marker that could indicate the raw material used. Whole casein from frozen river buffalo milk was separated using cation-exchange chromatography and sodium dodecyl sulfate-PAGE, and a protein component with an estimated molecular weight of 15.3 kDa was detected. This protein component was revealed in fresh river buffalo milk as a faint electrophoresis band, which drastically increased in intensity in refrigerated and frozen milk as well as in curd and was found to be associated with β-CN through hydrophobic interaction. By using matrix-assisted laser desorption/ionization-time of flight peptide mass mapping, this component was identified as the C-terminal fragment f(69-209) of β-CN (expected molecular weight of 15,748.8 Da). β-Casein f(69-209), originating from the early hydrolysis of Lys₆₈-Ser₆₉ by plasmin, has no counterpart in bovine milk. The increased rate of hydrolysis by plasmin toward the cleavage site Lys₆₈-Ser₆₉ has to be ascribed to the elevated proline content of the peptide 61-73. The favored production of β-CN f(69-209) has also drawn attention to the complementary proteose peptone β-CN f(1-68) that is presumed to play a physiological role in inducing milk secretion similar to that of β-CN f(1-29). The higher in vivo and in vitro production rate, compared with γ₁-CN formation, indicates that β-CN f(69-209) and its complementary fragment are candidate molecular markers to evaluate milk and curd freshness. We used indirect ELISA analysis based on the determination of remaining nonhydrolyzed β-CN to perform a quantitative evaluation of proteolysis.     

Effectiveness of mid-infrared spectroscopy for the prediction of detailed protein composition and contents of protein genetic variants of individual milk of Simmental cows

Mid-infrared (MIR) spectroscopy was used to predict the detailed protein composition of 1,517 milk samples of Simmental cows. Contents of milk protein fractions and genetic variants were quantified by reversed-phase HPLC. The most accurate predictions were those obtained for total protein, casein (CN), α_S1-CN, β-lactoglobulin (LG), glycosylated κ-CN, and whey protein content, which exhibited coefficients of determination between predicted and measured values in cross-validation (1-VR) ranging from 0.61 to 0.78. Less favorable were results for β-CN (1-VR = 0.53), α_S2-CN, and κ-CN (1-VR = 0.49). Neither the content of α-LA nor that of γ-CN was accurately predicted by MIR. Predicting the content of the most common milk protein genetic variants (κ-CN A and B; β-CN A¹, A², and B; and β-LG A and B) was unfeasible (1-VR <0.15 for the content of κ-CN genetic variants and 1-VR <0.01 for the content of β-CN variants). The best predictions were obtained for β-LG A and β-LG B contents (1-VR of 0.60 and 0.44, respectively). Results indicated that MIR is not applicable for predicting individual milk protein composition with high accuracy. However, MIR spectroscopy predictions may play a role as indicator traits in selective breeding to enhance milk protein composition. The genetic correlation between MIR spectroscopy predictions and measures of milk protein composition needs to be investigated, as it affects the suitability of MIR spectroscopy predictions as indicator traits in selective breeding.     

Effects of the detailed protein composition of milk on curd yield and composition measured by model micro-cheese curd making of individual milk samples

The effect of the contents of casein (CN) and whey protein fractions on curd yield (CY) and composition was estimated using 964 individual milk samples. Contents of α_S1-CN, α_S2-CN, β-CN, γ-CN, glycosylated κ-CN (Gκ-CN), unglycosylated κ-CN, β-LG, and α-LA of individual milk samples were measured using reversed-phase HPLC. Curd yield and curd composition were measured by model micro-cheese curd making using 25 mL of milk. Dry matter CY (DMCY) was positively associated with all casein fractions but especially with α_S1-CN and β-CN. Curd moisture decreased at increasing β-CN content and increased at increasing γ-CN and Gκ-CN content. Due to their associations with moisture, Gκ-CN and β-CN were the fractions with the greatest effect on raw CY, which decreased by 0.66% per 1-standard deviation (SD) increase in the content of β-CN and increased by 0.62% per 1-SD increase in the content of Gκ-CN. The effects due to variation in percentages of the casein fractions in total casein were less marked than those exerted by contents. A 1-SD increase in β-CN percentage in casein (+3.8% in casein) exerted a slightly negative effect on DMCY (β = ?0.05%). Conversely, increasing amounts of α_S1-CN percentage were associated with a small increase in DMCY. Hence, results suggest that, at constant casein and whey protein contents in milk, the DMCY depends to a limited extent on the variation in the α_S1-CN:β-CN ratio. κ-Casein percentage did not affect DMCY, indicating that the positive relationship detected between the content of κ-CN and DMCY can be attributed to the increase in total casein resulting from the increased amount of κ-CN and not to variation in κ-CN relative content. However, milk with increased Gκ-CN percentage in κ-CN also shows increased raw CY and produces curds with increased moisture content. Curd yield increased at increasing content and relative proportion of β-LG in whey protein, but this is attributable to an improved capacity of the curd to retain water. Results obtained in this study support the hypothesis that, besides variation in total casein and whey protein contents, variation in protein composition might affect the cheese-making ability of milk, but this requires further studies.     

Whole-genome association study for milk protein composition in dairy cattle

Our objective was to perform a genome-wide association study for content in bovine milk of α_S1-casein (α_S1-CN), α_S2-casein (α_S2-CN), β-casein (β-CN), κ-casein (κ-CN), α-lactalbumin (α-LA), β-lactoglobulin (β-LG), casein index, protein percentage, and protein yield using a 50K single nucleotide polymorphism (SNP) chip. In total, 1,713 Dutch Holstein-Friesian cows were genotyped for 50,228 SNP and a 2-step association study was performed. The first step involved a general linear model and the second step used a mixed model accounting for all family relationships. Associations with milk protein content and composition were detected on 20 bovine autosomes. The main genomic regions associated with milk protein composition or protein percentage were found on chromosomes 5, 6, 11, and 14. The number of chromosomal regions showing significant (false discovery rate <0.01) effects ranged from 3 for β-CN and 3 for β-LG to 12 for α_S2-CN. A genomic region on Bos taurus autosome (BTA) 6 was significantly associated with all 6 major milk proteins, and a genomic region on BTA 11 was significantly associated with the 4 caseins and β-LG. In addition, regions were detected that only showed a significant effect on one of the milk protein fractions: regions on BTA 13 and 22 with effects on α_S1-CN; regions on BTA 1, 9, 10, 17, 19, and 28 with effects on α_S2-CN; a region on BTA 6 with an effect on β-CN; regions on BTA 13 and 21 with effects on κ-CN; regions on BTA 1, 5, 9, 16, 17, and 26 with effects on α-LA; and a region on BTA 24 with an effect on β-LG. The proportion of genetic variance explained by the SNP showing the strongest association in each of these genomic regions ranged from <1% for α_S1-CN on BTA 22 to almost 100% for casein index on BTA 11. Variation associated with regions on BTA 6, 11, and 14 could in large part but not completely be explained by known protein variants of β-CN (BTA 6), κ-CN (BTA 6), and β-LG (BTA 11) or DGAT1 variants (BTA 14). Our results indicate 3 regions with major effects on milk protein composition, in addition to several regions with smaller effects involved in the regulation of milk protein composition.     

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 α_S1-casein (α_S1-CN) B, β-CN A² and β-lactoglobulin (β-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 α_S1-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 β-CN A², κ-CN E and A variants, as well as β-LG B, and the predominant composite genotype of β- 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 α_S1-, α_S2-, and β-CN. Compared with the group of WC milk samples, NC milk contained a higher fraction of α_S2-CN and α-lactalbumin (α-LA) but a lower fraction of α_S1-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 α_S2-CN and lower fraction of α_S1-CN 9P were related to NC milk. Further, a decrease in the frequency of the composite β-κ-CN genotype A²A²/AA through selective breeding could have a positive effect on milk coagulation properties.     

Effects of milk protein polymorphism and composition,casein micelle size and salt distribution on the milk coagulation properties in Norwegian Red cattle

Effects of milk protein polymorphism and composition, casein micelle size and salts distribution on the coagulation properties of milk from 99 Norwegian Red cattle (NRF) were studied. Genetic variants of α_S1-casein (CN), β-CN, κ-CN and β-lactoglobulin (LG) affected rennet coagulation properties of milk. Significant effects of κ-CN and the composite genotype α_S1-β-κ-CN were observed on acid coagulation properties. Relative concentrations of milk proteins were significantly affected by individual casein genotypes and the composite genotype of α_S1-β-κ-CN while, the relative concentration of β-LG was only affected by β-LG genotypes. The salts distribution in milk and the concentration of milk proteins affected both rennet and acid coagulation properties. Milk protein genotypes associated with better rennet coagulation, impaired the acid coagulation properties. However, α_S1-β-κ-CN BB-A¹A²-BE and BB-A²A²-BB were associated with poor rennet and acid coagulation properties. Breeding programs should focus on decreasing these genotypes in NRF cattle.     

SDS-PAGE of Proteins in Goat Milk Cheeses Ripened under Different Conditions

Proteolytic characteristics of five varieties of commercial goat milk cheeses and a cow milk Cheddar aged under different conditions were evaluated by SDS-PAGE and an advanced densitometry system. All fresh goat cheeses had distinctively lower intensities of α_S1-casein (CN) bands than those of cow milk Cheddar, whereas intensities of β-CN were much greater in the goat cheeses. The PAGE patterns clearly displayed α_S2-CN in all goat cheese, but it was negligible in cow milk Cheddar. The greater protein degradation in hard goat cheeses than cow milk Cheddar at 4°C and 22°C strongly correlated with water-soluble nitrogen compound concentrations and densitometric values of corresponding cheeses.     

Effect of processing methods and protein content of the concentrate on the properties of milk protein concentrate with 80% protein

In recent years, a large increase in the production of milk protein concentrates (MPC) has occurred. However, compared with other types of milk powders, few studies exist on the effect of key processing parameters on powder properties. In particular, it is important to understand if key processing parameters contribute to the poor solubility observed during storage of high-protein MPC powders. Ultrafiltration (UF) and diafiltration (DF) are processing steps needed to reduce the lactose content of concentrates in the preparation of MPC with a protein content of 80% (MPC80). Evaporation is sometimes used to increase the TS content of concentrates before spray drying, and some indications exist that inclusion of this processing step may affect protein properties. In this study, MPC80 powders were manufactured by 2 types of concentration methods: membrane filtration with and without the inclusion of an evaporation step. Different concentration methods could affect the mineral content of MPC powders, as soluble salts can permeate the UF membrane, whereas no mineral loss occurs during evaporation, although a shift in calcium equilibrium toward insoluble forms may occur at high protein concentration levels. It is more desirable from an energy efficiency perspective to use higher total solids in concentrates before drying, but concerns exist about whether a higher protein content would negatively affect powder functionality. Thus, MPC80 powders were also manufactured from concentrates that had 3 different final protein concentrations (19, 21, and 23%; made from 1 UF retentate using batch recirculation evaporation, a similar concentration method). After manufacture, powders were stored for 6 mo at 30°C to help understand changes in MPC80 properties that might occur during shelf-life. Solubility and foaming properties were determined at various time points during high-temperature powder storage. Inclusion of an evaporation step, as a concentration method, resulted in MPC80 that had higher ash, total calcium, and bound calcium (of rehydrated powder) contents compared to concentration with only membrane filtration. Concentration method did not significantly affect the bulk (tapped) density, solubility, or foaming properties of the MPC powders. Powder produced from concentrate with 23% protein content exhibited a higher bulk density and powder particle size than powder produced from concentrate that had 19% protein. The solubility of MPC80 powder was not influenced by the protein content of the concentrate. The solubility of all powders significantly decreased during storage at 30°C. Higher protein concentrations in concentrates resulted in rehydrated powders that had higher viscosities (even when tested at a constant protein concentration). The protein content of the concentrate did not significantly affect foaming properties. Significant changes in the mineral content are used commercially to improve MPC80 solubility. However, although the concentration method did produce a small change in the total calcium content of experimental MPC80 samples, this modification was not sufficiently large enough (<7%) to influence powder solubility.     

Changes in the physical properties,solubility, and heat stability of milk protein concentrates prepared from partially acidified milk

A limiting factor in using milk protein concentrates (MPC) as a high-quality protein source for different food applications is their poor reconstitutability. Solubilization of colloidal calcium phosphate (CCP) from casein micelles during membrane filtration (e.g., through acidification) may affect the structural organization of these protein particles and consequently the rehydration and functional properties of the resulting MPC powder. The main objective of this study was to investigate the effects of acidification of milk by glucono-δ-lactone (GDL) before ultrafiltration (UF) on the composition, physical properties, solubility, and thermal stability (after reconstitution) of MPC powders. The MPC samples were manufactured in duplicate, either by UF (65% protein, MPC65) or by UF followed by diafiltration (80% protein, MPC80), using pasteurized skim milk, at either the native milk pH (~pH 6.6) or at pH 6.0 after addition of GDL, followed by spray drying. Samples of different treatments were reconstituted at 5% (wt/wt) protein to compare their solubility and thermal stability. Powders were tested in duplicate for basic composition, calcium content, reconstitutability, particle size, particle density, and microstructure. Acidification of milk did not have any significant effect on the proximate composition, particle size, particle density, or surface morphology of the MPC powders; however, the total calcium content of MPC80 decreased significantly with acidification (from 1.84 ± 0.03 to 1.59 ± 0.03 g/100 g of powder). Calcium-depleted MPC80 powders were also more soluble than the control powders. Diafiltered dispersions were significantly less heat stable (at 120°C) than UF samples when dissolved at 5% solids. The present work contributes to a better understanding of the differences in MPC commonly observed during processing.     

Structural equation modeling for unraveling the multivariate genomic architecture of milk proteins in dairy cattle

The aims of this study were to investigate potential functional relationships among milk protein fractions in dairy cattle and to carry out a structural equation model (SEM) GWAS to provide a decomposition of total SNP effects into direct effects and effects mediated by traits that are upstream in a phenotypic network. To achieve these aims, we first fitted a mixed Bayesian multitrait genomic model to infer the genomic correlations among 6 milk nitrogen fractions [4 caseins (CN), namely κ-, β-, α_S1-, and α_S2-CN, and 2 whey proteins, namely β-lactoglobulin (β-LG) and α-lactalbumin (α-LA)], in a population of 989 Italian Brown Swiss cows. Animals were genotyped with the Illumina BovineSNP50 Bead Chip v.2 (Illumina Inc.). A Bayesian network approach using the max-min hill-climbing (MMHC) algorithm was implemented to model the dependencies or independence among traits. Strong and negative genomic correlations were found between β-CN and α_S1-CN (?0.706) and between β-CN and κ-CN (?0.735). The application of the MMHC algorithm revealed that κ-CN and β-CN seemed to directly or indirectly influence all other milk protein fractions. By integrating multitrait model GWAS and SEM-GWAS, we identified a total of 127 significant SNP for κ-CN, 89 SNP for β-CN, 30 SNP for α_S1-CN, and 14 SNP for α_S2-CN (mostly shared among CN and located on Bos taurus autosome 6) and 15 SNP for β-LG (mostly located on Bos taurus autosome 11), whereas no SNP passed the significance threshold for α-LA. For the significant SNP, we assessed and quantified the contribution of direct and indirect paths to total marker effect. Pathway analyses confirmed that common regulatory mechanisms (e.g., energy metabolism and hormonal and neural signals) are involved in the control of milk protein synthesis and metabolism. The information acquired might be leveraged for setting up optimal management and selection strategies aimed at improving milk quality and technological characteristics in dairy cattle.     

Identification of rare genetic variants of the αS-caseins in milk from native Norwegian dairy breeds and comparison of protein composition with milk from high-yielding Norwegian Red cows

Several factors influence the composition of milk. Among these, genetic variation within and between cattle breeds influences milk protein composition, protein heterogeneity, and their posttranslational modifications. Such variations may further influence technological properties, which are of importance for the utilization of milk into dairy products. Furthermore, these potential variations may also facilitate the production of differentiated products (e.g., related to specific breeds or specific genetic variants). The objective of this study was to investigate the genetic variation and relative protein composition of the major proteins in milk from 6 native Norwegian dairy breeds representing heterogeneity in geographical origin, using the modern Norwegian breed, Norwegian Red, as reference. In total, milk samples from 144 individual cows were collected and subjected to liquid chromatography-electrospray ionization/mass spectrometry–based proteomics for identification of genetic and posttranslational modification isoforms of the 4 caseins (α_S1-CN, α_S2-CN, β-CN, κ-CN) and the 2 most abundant whey proteins (α-lactalbumin and β-lactoglobulin). Relative quantification of these proteins and their major isoforms, including phosphorylations of α_S1-CN and glycosylation of κ-CN, were determined based on UV absorbance. The presence and frequency of genetic variants of the breeds were found to be very diverse and it was possible to identify rare variants of the CN, which, to our knowledge, have not been identified in these breeds before. Thus, α_S1-CN variant D was identified in low frequency in 3 of the 6 native Norwegian breeds. In general, α_S1-CN was found to be quite diverse between the native breeds, and the even less frequent A and C variants were furthermore detected in 1 and 5 of the native breeds, respectively. The α_S1-CN variant C was also identified in samples from the Norwegian Red cattle. The variant E of κ-CN was identified in 2 of the native Norwegian breeds. Another interesting finding was the identification of α_S2-CN variant D, which was found in relatively high frequencies in the native breeds. Diversity in more common protein genetic variants were furthermore observed in the protein profiles of the native breeds compared with milk from the high-yielding Norwegian Reds, probably reflecting the more diverse genetic background between the native breeds.