Validation of a new reversed-phase high-performance liquid chromatography method for separation and quantification of bovine milk protein genetic variants

Glycation of goat milk with different casein-to-whey protein ratios and its effects on simulated infant digestion

This research compared the effects of dry heating on the digestion of goat milk proteins with different casein-to-whey ratios (40% casein, C40 and 80% casein, C80). The glycation markers of heated samples were determined by LC-MS. Heating at 60 °C for 8 h induced early glycation while heating at 60 °C for 72 h induced advanced glycation. Unheated C80 samples showed a higher digestibility than unheated C40 samples, which may be due to their higher protein solubility. After dry heating for 72 h, no significant difference in digestibility was observed between C80 and C40 samples. Heating for 72 h decreased the digestibility of C40 samples compared to unheated samples, probably due to glycation, while protein aggregation was the main reason for the reduced digestibility of heated C80 samples. Overall, this study showed that dry heating for 72 h induced a lower digestibility of C80 and C40 samples, although with different underlying mechanisms.

Physicochemical properties of micellar casein retentates generated at different microfiltration temperatures

Processing temperature has a significant influence on the composition and functionality of the resulting streams following microfiltration (MF) of skim milk. In this study, MF and diafiltration (DF) were performed at 4 or 50°C to produce β-casein (β-CN)-depleted and nondepleted (i.e., native casein profile) micellar casein isolate retentates, respectively. Microfiltration combined with extensive DF resulted in a 40% depletion of β-CN at 4°C, whereas no β-CN depletion occurred at 50°C. Microfiltration at 4°C led to higher transmission of calcium into permeates, with retentate generated at 4°C containing less total calcium compared with retentate generated at 50°C, based on the volume of retentate remaining. Higher heat stability at 120°C was measured for retentates generated at 4°C compared with those at 50°C, across all pH values measured. Retentates generated at 4°C also had significantly lower ionic calcium values at each pH compared with those generated at 50°C. Higher apparent viscosities at 4°C were measured for retentates generated at 4°C compared with retentates generated at 50°C, likely due to increased voluminosity of β-CN-depleted casein micelles. The results of this study provide new information on how changing the composition of MF retentate, by appropriate control of processing temperature and DF, can alter physicochemical properties of casein micelles, with potential implications for ingredient functionality.

Effect of composition, casein genetic variants and glycosylation degree on bovine milk whipping properties

This study investigated the individual and combined effects of ĸ-Casein (ĸ-CN; AA, AB, BB), β-Casein (β-CN; A1A1, A1A2, A2A2) and high and low ratios of glycosylated ĸ-CN to total ĸ-CN, referred to as the glycosylation degree (GD), on bovine cream whipping properties. The genetic variants of individual cows were identified using reversed-phase high-performance liquid chromatography (RP-HPLC) and verified through liquid chromatography-mass spectrometry (LC-MS). A previously discovered relationship between days-in-milk and GD was validated and used to obtain high and low GD milk. Whipped creams were created through the mechanical agitation of fat standardised cream from milk of different ĸ-CN, β-CN, and GD combinations, and whipping properties (the ability to whip, overrun, whipping time and firmness) were evaluated. No significant correlation was measured in whipping properties for cream samples from milks with different ĸ-CN and β-CN genetic variants. However, 80 % of samples exhibiting good whipping properties (i.e., the production of a stiffened peak) were from milk with low GD suggesting a correlation between whipping properties and levels of glycosylation. Moreover, cream separated from skim milk of larger casein micelle size showed superior whipping properties with shorter whipping times (<5 min), and higher firmness and overrun. Milk fat globule (MFG) size, on the other hand, did not affect whipping properties. Results indicate that the GD of κ-CN and casein micelle size may play a role in MFG adsorption at the protein and air interface of air bubbles formed during whipping; hence, they govern the dynamics of fat network formation and influencing whipping properties.

Advances in separation and identification of biologically important milk proteins and peptides

Milk is a rich source of biologically important proteins and peptides. In addition, milk contains a variety of extracellular vesicles (EVs), including exosomes, that carry their own proteome cargo. EVs are essential for cell-cell communication and modulation of biological processes. They act as nature carriers of bioactive proteins/peptides in targeted delivery during various physiological and pathological conditions. Identification of the proteins and protein-derived peptides in milk and EVs and recognition of their biological activities and functions had a tremendous impact on food industry, medicine research, and clinical applications. Advanced separation methods, mass spectrometry (MS)-based proteomic approaches and innovative biostatistical procedures allowed for characterization of milk protein isoforms, genetic/splice variants, posttranslational modifications and their key roles, and contributed to novel discoveries. This review article discusses recently published developments in separation and identification of bioactive proteins/peptides from milk and milk EVs, including MS-based proteomic approaches.

Effect of Buffalo Breed on the Detailed Milk Composition in Guangxi, China

Buffalo is the second source of milk in the world, and its milk is rich in nutritive components. It is well-known that breed influences milk composition. This work aimed to compare the detailed milk composition of three buffalo breeds (Murrah, Nili-Ravi, and Mediterranean) housed under the same environmental conditions. Mediterranean buffalo milk showed a significantly higher content of fat, protein, and some fatty acids. Moreover, the milk from the Mediterranean breed was characterized by the highest content of sphingomyelin (SM), cholesterol, and lanosterol. However, the Murrah buffalo milk contained the highest amount of total unsaturated fatty acids, phosphatidylinositol, and whey proteins. Furthermore, the Nili-Ravi buffalo milk was characterized by the highest content of total saturated fatty acids, phosphatidylglycerol, squalene, lathosterol, stigmasterol, beta-sitosterol, and casein fractions. Nevertheless, the lactose and amino acid profiles of the milk remained almost similar across the three buffalo breeds. The generated results in this study enable a comprehensive understanding of the milk constituent variability that is linked to buffalo breeds, which may support the acquirement of essential scientific knowledge on milk ingredient-processing interactions that will offer a foundation of knowledge for Chinese dairy processors in terms of milk processability and innovation.

Effect of plasmin on casein hydrolysis and textural properties of rennet-induced model cheeses

Plasmin plays an important role in casein hydrolysis during cheese ripening, which may influence the properties of the casein network and the texture of the final product. In view of this, the relation between plasmin-induced casein hydrolysis and textural changes of cheese during ripening was investigated in this study. Four batches of model cheese with different concentrations of added plasmin (0, 0.4, 0.6 and 1.0 μL/g milk) were prepared, and were stored for 12 weeks at 16 °C. During this period, plasmin activity, casein hydrolysis, textural properties and other compositional characteristics (pH, dry matter) were determined. Our results show that the addition of plasmin had significant effect on both the degree and the pattern of proteolysis. As a result, cheeses with different plasmin content showed different textural properties. With increased plasmin concentration, Young's modulus, hardness, resilience and cohesion decreased, while brittleness increased. All textural properties showed linear relations with the degree of casein hydrolysis, and logarithmic relations with the percentage of intact casein fractions. At the beginning of ripening, only slight changes in textural properties were found, although a substantial part (40-60 %) of the casein fractions was already been broken down. When ripening progressed, ongoing proteolysis significantly weakened the protein network and consequently led to noticeable textural changes. Model cheeses became softer, more brittle and less elastic. The knowledge gained from this study provide new insights in the changes of different textural parameters of model cheese. This will help to optimize the existing products and create new ones.

An approach on detection, quantification, technological properties, and trends market of A2 cow milk

The genetic variant A2 β-casein integrates the casein protein group in milk and has been often associated with positive health outcomes. Therefore, this review explores the present understanding of A2 β-casein, including detection methods and the market trends for dairy from A2 milk. Also, the interaction of A2 β-casein with αs₁-casein and κ-casein genotypes was examined in terms of technological impacts on A2 milk. A limited number of preliminary studies has aimed to investigate the sensorial and technological impacts of β-casein variants in milk matrices, for instance, in yogurt and other derivatives. Nevertheless, considering studies carried out so far, it is concluded that the manufacture of dairy products from A2 milk is perfectly feasible, as the products presented slight differences when compared to those derived from traditional milk. In one of the works, sensitive drops in rennet coagulation time and curd firmness values were observed in cheese traits. However, it is relevant to point out that variant A of κ-casein plays a negative role in the coagulation features of milk. Therefore, alterations in the pattern of cheese-making properties are not uniquely related to β-casein variants. Attempts to produce A2 β-casein in laboratory (non-natural source), through biosynthesis, for example, have not been found so far. This knowledge gap offers a promising area for future studies concerning proteins and bioactive peptide production.

The role of glycosylation in amyloid fibril formation of bovine κ-casein

In order to explore the functions of glycosylation of κ-Casein (κ-CN) in bovine milk, unglycosylated (UG) and twice glycosylated (2G) forms of κ-CN B were purified by selective precipitation followed by anion exchange chromatography from κ-CN BB milk and tested for their amyloid fibril formation and morphology, oligomerisation states and protein structure. The diameter of self-assembled κ-CN B aggregates of both glyco-form were shown for the first time to be in the same 26.0-28.7 nm range for a 1 mg mL^-1 solution. The presence of two bound glycans in the protein structure of 2G κ-CN B led to a greater increase in the maximum amyloid fibril formation rate with increasing protein concentration and a difference in both length (82.0 ± 29.9 vs 50.3 ± 13.7 nm) and width (8.6 ± 2.1 vs 13.9 ± 2.5 nm) for fibril morphology compared to UG κ-CN B. The present results suggest that amyloid fibril formation proceeds at a slow but steady rate via the self-assembly of dissociated, monomeric κ-CN B proteins at concentrations of 0.22-0.44 mg mL^-1. However amyloid fibril formation proceeds more rapidly via the assembly of either aggregated κ-CN present in a micelle-like form or dissociated monomeric κ-CN, packed into reorganised formational structures above the critical micellar concentration to form fibrils of differing width. The degree of glycosylation has no effect on the polarity of the adjacent environment, nor non-covalent and disulphide interactions between protein molecules when in the native form. Yet glycosylation can influence protein folding patterns of κ-CN B leading to a reduced tryptophan intrinsic fluorescence intensity for 2G compared to UG κ-CN B. These results demonstrate that glycosylation plays an important role in the modulation of aggregation states of κ-CN and contributes to a better understanding of the role of glycosylation in the formation of amyloid fibrils from intrinsically disordered proteins.

Proteomics Characterization of Food-Derived Bioactive Peptides with Anti-Allergic and Anti-Inflammatory Properties

Bioactive peptides are found in foods and dietary supplements and are responsible for health benefits with applications in human and animal medicine. The health benefits include antihypertensive, antimicrobial, antithrombotic, immunomodulatory, opioid, antioxidant, anti-allergic and anti-inflammatory functions. Bioactive peptides can be obtained by microbial action, mainly by the gastrointestinal microbiota from proteins present in food, originating from either vegetable or animal matter or by the action of different gastrointestinal proteases. Proteomics can play an important role in the identification of bioactive peptides. High-resolution mass spectrometry is the principal technique used to detect and identify different types of analytes present in complex mixtures, even when available at low concentrations. Moreover, proteomics may provide the characterization of epitopes to develop new food allergy vaccines and the use of immunomodulating peptides to induce oral tolerance toward offending food allergens or even to prevent allergic sensitization. In addition, food-derived bioactive peptides have been investigated for their anti-inflammatory properties to provide safer alternatives to nonsteroidal anti-inflammatory drugs (NSAIDs). All these bioactive peptides can be a potential source of novel drugs and ingredients in food and pharmaceuticals. The following review is focused on food-derived bioactive peptides with antiallergic and anti-inflammatory properties and summarizes the new insights into the use of proteomics for their identification and quantification.

Prediction of fresh and ripened cheese yield using detailed milk composition and udder health indicators from individual Brown Swiss cows

The composition of raw milk is of major importance for dairy products, especially fat, protein, and casein (CN) contents, which are used worldwide in breeding programs for dairy species because of their role in human nutrition and in determining cheese yield (%CY). The aim of the study was to develop formulas based on detailed milk composition to disentangle the role of each milk component on %CY traits. To this end, 1,271 individual milk samples (1.5 L/cow) from Brown Swiss cows were processed according to a laboratory model cheese-making procedure. Fresh %CY (%CY_CURD), total solids and water retained in the fresh cheese (%CY_SOLIDS and %CY_WATER), and 60-days ripened cheese (%CY_RIPENED) were the reference traits and were used as response variables. Training-testing linear regression modeling was performed: 80% of observations were randomly assigned to the training set, 20% to the validation set, and the procedure was repeated 10 times. Four groups of predictive equations were identified, in which different combinations of predictors were tested separately to predict %CY traits: (i) basic composition, i.e., fat, protein, and CN, tested individually and in combination; (ii) udder health indicators (UHI), i.e., fat + protein or CN + lactose and/or somatic cell score (SCS); (iii) detailed protein profile, i.e., fat + protein fractions [CN fractions, whey proteins, and nonprotein nitrogen (NPN) compounds]; (iv) detailed protein profile + UHI, i.e., fat + protein fractions + NPN compounds and/or UHI. Aside from the positive effect of fat, protein, and total casein on %CY, our results allowed us to disentangle the role of each casein fraction and whey protein, confirming the central role of β-CN and κ-CN, but also showing α-lactalbumin (α-LA) to have a favorable effect, and β-lactoglobulin (β-LG) a negative effect. Replacing protein or casein with individual milk protein and NPN fractions in the statistical models appreciably increased the validation accuracy of the equations. The cheese industry would benefit from an improvement, through genetic selection, of traits related to cheese yield and this study offers new insights into the quantification of the influence of milk components in composite selection indices with the aim of directly enhancing cheese production.

Characterization of the genetic polymorphism linked to the β-casein A1/A2 alleles using different molecular and biochemical methods

The 2 major subvariants of β-casein (A1 and A2), coded by CSN2 gene, have received great interest in the last decade both from the scientific community and the dairy sector due to their influence on milk quality. The consumption of the A1 variant, compared with the A2 variant, has a potential negative effect on human health after its digestion but, at the same time, its presence improves the milk technological properties. The aim of the present study was to compare the best method in terms of time required, costs, and technical engagement for the identification of β-casein A1 and A2 variants (homozygous and heterozygous animals) in milk to offer a reliable service for large-scale screening studies. Two allele-specific PCR procedures, namely RFLP-PCR and amplification refractory mutation system (ARMS-PCR), and one biochemical technique (HPLC) were evaluated and validated through sequencing. Manual and automated DNA extraction protocols from milk somatic cells were also compared. Automated DNA extraction provided better yield and purity. Chromatographic analysis was the most informative and the cheapest method but unsuitable for large-scale studies due to lengthy procedures (45 min per sample). Both allele-specific PCR techniques proved to be fast and reliable for differentiating between A1 and A2 variants but more expensive than HPLC analysis. Specifically, RFLP-PCR was the most expensive and labor-demanding among the evaluated techniques, whereas ARMS-PCR was the fastest while also requiring less technical expertise. Overall, automated extraction of DNA from milk matrix combined with ARMS-PCR is the most suitable technique to provide genetic characterization of the CSN2 gene on a large scale.

What is the impact of amino acid mutations in the primary structure of caseins on the composition and functionality of milk and dairy products?

The impact of amino acid mutations within the peptide structure of bovine milk protein is important to understand as it can effect processability and subsequently effect its physiological properties. Genetic polymorphisms of bovine caseins can influence the chemical, structural, and technological properties, including casein micelle morphology, calcium distribution, network creation upon gelation, and surface activity. The A1 and A2 genetic variants of β-casein have recently acquired growing attention from both academia and industry, prompting new developments in the area. The difference between these two genetic variants is the inclusion of either proline in β-casein A2 or histidine in β-casein A1 at position 67 in the peptide chain. The aim of this review was to examine the extent to which milk and ingredient functionality is influenced by β-casein phenotype. One of the main findings of this review was although β-casein A1 was found to be the dominant variant in milks with superior acid gelation and rennet coagulation properties, milks comprised of β-casein A2 possessed greater emulsion and foam formation capabilities. The difference in the casein micelle assembly, hydrophobicity, and chaperone activity of caseins may explain the contrast in the functionality of milks containing β-casein from either A1 or A2 families. This review provides new insights into the subtle variations in the physicochemical properties of bovine milks, which could potentially support dairy producers in the development of new dairy products with different functional properties.

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Impact of β- and other caseins on the casein micelle structure and functionality.

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Proline and histidine in β-caseins play a key role in casein micelle conformation.

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Chaperone activity of β-casein A2 towards heat-induced aggregation of whey protein.

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Gels prepared of milks with β-casein A1 possess a denser and firmer structure.

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Ordered structure of β-casein A2 led to improved emulsion and foam formation.

Characterization of a Commercial Whey Protein Hydrolysate and Its Use as a Binding Agent in the Whey Protein Isolate Agglomeration Process

The first objective of this study was to characterize the chemical properties of three lots of whey protein hydrolysate (WPH) obtained from a commercial manufacturer. The degree of hydrolysis (DH) of WPH was between 13.82 and 15.35%, and was not significantly (p > 0.05) different between the batches. From MALDI-TOF, 10 to 13 different peptides were observed in the range of 2.5−5 kDa and 5−8 kDa, respectively. The second objective of the study was to evaluate the effectiveness of WPH as a binder in whey protein isolate (WPI) wet agglomeration. For this purpose, a 3 × 3 × 2 factorial design was conducted with pre-wet mass (60, 100, and 140 g), WPH concentration (15, 20, and 25%), and flow rate (4.0 and 5.6 mL·min−1) as independent variables. WPI agglomeration was carried out in a top-spray fluid bed granulator (Midi-Glatt, Binzen, Germany). Agglomerated WPI samples were stored at 25 °C and analyzed for moisture content (MC), water activity, relative dissolution index (RDI), and emulsifying capacity. Pre-wet mass, flow rate, and the WPH concentration had a significant (p < 0.05) effect on the MC. Moreover, all interactions among the main effects had also a significant (p < 0.05) effect on MC. High MC and water activity were observed for the treatments with a higher pre-wet volume and higher flow rate, which also resulted in clumping of the powders. The treatment with the 60 g pre-wet mass, 20% WPH concentration, and 5.6 mL·min−1 flow rate combination had the highest RDI among all the samples. In conclusion, WPH can be used as a potential alternative to soy lecithin in WPI wet agglomeration.

A fluorescence detection method for the determination of β-lactoglobulin in foods

A fluorescence detection method based on quantum dot-aptamer-graphene oxide probes (QD-Apt-GO) was developed to detect β-lactoglobulin (β-LG) in foods. When β-LG was present in the samples, it specifically bound to the aptamer, inhibiting the binding of probes to graphene oxide (GO), and the fluorescence of the probes could be detected. When β-LG was not present, the probes could bind to GO through π-π stacking, and the fluorescence was consequently quenched. The detection range of the optimized assay for β-LG detection was 0.36-500 mg L^-1. The limit of detection (LOD) for β-LG was 96.91 μg L^-1. The method was also validated for food sample detection. In the spike and recovery experiments of Neocate amino acid infant formula, infant millet cookies, and infant rice porridge, the recoveries were in the range of 83.33-114.53%, which met the required range of the addition recoveries. At the same time, the results were consistent with those of commercial ELISA kits. Three types of random food products purchased from a local market were analyzed for β-LG via the developed assay and using a commercial ELISA kit. The results showed good accuracy and consistency between the proposed method and the commercial ELISA kit.

Role of CSN2, CSN3, and BLG genes and the polygenic background in the cattle milk protein profile

To devise better selection strategies in dairy cattle breeding programs, a deeper knowledge of the role of the major genes encoding for milk protein fractions is required. The aim of the present study was to assess the effect of the CSN2, CSN3, and BLG genotypes on individual protein fractions (α_S1-CN, α_S2-CN, β-CN, κ-CN, β-LG, α-LA) expressed qualitatively as percentages of total nitrogen content (% N), quantitatively as contents in milk (g/L), and as daily production levels (g/d). Individual milk samples were collected from 1,264 Brown Swiss cows reared in 85 commercial herds in Trento Province (northeast Italy). A total of 989 cows were successfully genotyped using the Illumina Bovine SNP50 v.2 BeadChip (Illumina Inc.), and a genomic relationship matrix was constructed using the 37,519 SNP markers obtained. Milk protein fractions were quantified and the β-CN, κ-CN, and β-LG genetic variants were identified by reversed-phase HPLC (RP-HPLC). All protein fractions were analyzed through a Bayesian multitrait animal model implemented via Gibbs sampling. The effects of days in milk, parity order, and the CSN2, CSN3, and BLG genotypes were assigned flat priors in this model, whereas the effects of herd and animal additive genetic were assigned Gaussian prior distributions, and inverse Wishart distributions were assumed for the respective co-variance matrices. Marginal posterior distributions of the parameters of interest were compared before and after the inclusion of the effects of the 3 major genes in the model. The results showed that a high portion of the genetic variance was controlled by the major genes. This was particularly apparent in the qualitative protein profile, which was found to have a higher heritability than the protein fraction contents in milk and their daily yields. When the genes were included individually in the model, CSN2 was the major gene controlling all the casein fractions except for κ-CN, which was controlled directly by the CSN3 gene. The BLG gene had the most influence on the 2 whey proteins. The genetic correlations showed the major genes had only a small effect on the relationships between the protein fractions, but through comparison of the correlation coefficients of the proteins expressed in different ways they revealed potential mechanisms of regulation and competitive synthesis in the mammary gland. The estimates for the effects of the CSN2 and CSN3 genes on protein profiles showed overexpression of protein synthesis in the presence of the B allele in the genotype. Conversely, the β-LG B variant was associated with a lower concentration of β-LG compared with the β-LG A variant, independently of how the protein fractions were expressed, and it was followed by downregulation (or upregulation in the case of the β-LG B) of all other protein fractions. These results should be borne in mind when seeking to design more efficient selection programs aimed at improving milk quality for the efficiency of dairy industry and the effect of dairy products on human health.

Concentration, purification and quantification of milk protein residues following cleaning processes using a combination of SPE and RP-HPLC

Detection and quantification of milk protein residues can be of utmost importance for validation of cleaning process efficiency in removing even traces of residues as well as quality assurance and product safety. However, currently available assays cannot provide a combination of high sensitivity and a simultaneous quantification of the individual milk proteins. Furthermore, a low protein-to-protein-variability and high compatibility with other reagents such as residual cleaning agents (e.g. surfactants) cannot be ensured. Therefore, a new method was developed comprised of a pre-concentration of proteins by solid-phase extraction and optimisation of the sensitivity of an existing reversed-phase high performance liquid chromatography method for the separate quantification of bovine milk proteins κ-Casein, α_S2-Casein, α_S1-Casein, β-Casein, α-Lactalbumin, and β-Lactoglobulin. Hereby, solid-phase extraction enables robust and reproducible purification and concentration of protein residues with a high protein recovery rate and flexible adjustment of concentration factors. The increased sensitivity of the reversed-phase high performance liquid chromatography method was achieved by changes in the measurement wavelength and guanidine buffer concentration. This new method enables reproducible concentration, purification and quantification of protein concentrations below 7 ng mL⁻¹ and thus can be used to detect milk protein residues in highly diluted aqueous systems.•

Concentration, purification and quantification of milk protein residues with a high recovery rate of proteins (> 94%) and high reproducibility (coefficient of variation (CV) < 3.0%)

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Flexible adjustment of sample volumes allows the utilisation of high concentration factors (≤ 500) without compromising the recovery rate of proteins (recovery rate of proteins decreases by 2.74% per 100 CF)

Effects of the thermal denaturation degree of a whey protein isolate on the strength of acid milk gels and the dissociation of κ-casein

In this study, the effects of the degree of thermal denaturation of whey protein (WP) added to milk on the dissociation of κ-casein from casein micelles were investigated, since they are related to the strength of acid milk gel and its factors. Acid milk gels were prepared by heating thermally denatured WP isolate (WPI) and undenatured milk mixtures and treating them with glucono-δ-lactone as a coagulant. The strength of these gels was negatively correlated with the WPI denaturation degree and strongly positively correlated with the extent of κ-casein dissociation from casein micelles. This behavior was ascribed to the fact that α-lactalbumin (α-La) and β-lactoglobulin (β-Lg) contained in WPI denatured after heating and engaged in disulfide bond formation with each other. With an increase in the degree of denaturation and disulfide bond formation, the bonding between β-lactoglobulin and κ-casein was suppressed to decrease the amount of κ-casein-WPI complexes. When β-Lg forms SS bonds with α-La, the number of highly reactive, free SH groups decreases, which complicates the formation of SS bridges between β-Lg and κ-casein. Thus, the denaturation degree of WPI largely determined the degree of κ-casein dissociation from casein micelles and, consequently, the strength of acid milk gels. Adding WP to milk increases the strength of acid milk gel, and it can be controlled by changing the degree of thermal denaturation of the WP. Furthermore, it was clarified for the first time that the dissociation of κ-casein from casein micelles influences this effect. Further studies are needed to elucidate the structural features of κ-casein-dissociated micelles.

Intracellular Staphylococcus aureus Infection Decreases Milk Protein Synthesis by Preventing Amino Acid Uptake in Bovine Mammary Epithelial Cells

Staphylococcus aureus (S. aureus) is one of the main pathogens in cow mastitis, colonizing mammary tissues and being internalized into mammary epithelial cells, causing intracellular infection in the udder. Milk that is produced by cows that suffer from mastitis due to S. aureus is associated with decreased production and changes in protein composition. However, there is limited information on how mastitis-inducing bacteria affect raw milk, particularly with regard to protein content and protein composition. The main purpose of this work was to examine how S. aureus infection affects milk protein synthesis in bovine mammary epithelial cells (BMECs). BMECs were infected with S. aureus, and milk protein and amino acid levels were determined by ELISA after S. aureus invasion. The activity of mTORC1 signaling and the transcription factors NF-κB and STAT5 and the expression of the amino acid transporters SLC1A3 and SLC7A5 were measured by western blot or immunofluorescence and RT-qPCR. S. aureus was internalized by BMECs in vitro, and the internalized bacteria underwent intracellular proliferation. Eight hours after S. aureus invasion, milk proteins were downregulated, and the level of BMECs that absorbed Glu, Asp, and Leu from the culture medium and the exogenous amino acids induced β-casein synthesis declined. Further, the activity of mTORC1 signaling, NF-κB, and STAT5 was impaired, and SLC1A3 and SLC7A5 were downregulated. Eight hours of treatment with 100 nM rapamycin inhibited NF-κB and STAT5 activity, SLC1A3 and SLC7A5 expression, and milk protein synthesis in BMECs. Thus mTORC1 regulates the expression of SLC1A3 and SLC7A5 through NF-κB and STAT5. These findings constitute a model by which S. aureus infection suppresses milk protein synthesis by decreasing amino acids uptake in BMECs.

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.

Protein Quality in Infant Formulas Marketed in Brazil: Assessments on Biodigestibility, Essential Amino Acid Content and Proteins of Biological Importance

Infant formulas, designed to provide similar nutritional composition and performance to human milk, are recommended when breastfeeding is not enough to provide for the nutritional needs of children under 12 months of age. In this context, the present study aimed to assess the protein quality and essential amino acid content of both starting (phase 1) and follow-up (phase 2) formulas from different manufacturers. The chemical amino acid score and protein digestibility corrected by the amino acid score were calculated. The determined protein contents in most formulas were above the maximum limit recommended by FAO and WHO guidelines and at odds with the protein contents declared in the label. All infant formulas contained lactoferrin (0.06 to 0.44 g·100 g⁻¹) and α-lactalbumin (0.02 to 1.34 g·100 g⁻¹) below recommended concentrations, whereas ĸ-casein (8.28 to 12.91 g·100 g⁻¹), α-casein (0.70 to 2.28 g·100 g⁻¹) and β-lactoglobulin (1.32 to 4.19 g·100 g⁻¹) were detected above recommended concentrations. Essential amino acid quantification indicated that threonine, leucine and phenylalanine were the most abundant amino acids found in the investigated infant formulas. In conclusion, infant formulas are still unconforming to nutritional breast milk quality and must be improved in order to follow current global health authority guidelines.

Compositional Characteristics of Mediterranean Buffalo Milk and Whey

The main objective of this review is to summarize the compositional characteristics and the health and functional properties of Mediterranean buffalo milk and whey derived from mozzarella cheese production. Several studies have investigated the composition of buffalo milk and in particular its fat, protein, and carbohydrates contents. These characteristics may change depending on the breed, feeding regime, and rearing system of the animals involved in the study, and also with the seasons. In particular, buffalo milk showed a higher nutritional value and higher levels of proteins, vitamins, and minerals when compared to milks produced by other animal species. Additionally, buffalo milk contains beneficial compounds such as gangliosides that can provide antioxidant protection and neuronal protection, and can improve bone, heart, and gastrointestinal health in humans.

"A2 milk" authentication using isoelectric focusing and different PCR techniques

Genetic variants of milk proteins have attracted great interest for decades as they are related to important issues such as the composition and technological properties of milk. More recently, an "A1/A2 hypothesis" was developed saying that β-casein variant A1 may be a dietary risk factor for cardiovascular diseases, type 1 diabetes, sudden infant death syndrome and neurological disorders due to the release of β-casomorphin-7, whereas no evidence for such adverse effects was assumed for β-casein A2. Thus, the aim of this study was to adapt and establish analytical methods for the identification of genetic variants of β-casein using isoelectric focusing of milk proteins as well as appropriate PCR techniques. Allele-specific polymerase chain reaction (AS-PCR) proved to be a reliable method for differentiating most common β-casein variants (A1, A2, B, C), amplification-created restriction site (ACRS)-PCR using three different restriction enzymes allowed also the detection of variant A3, and the restriction fragment length polymorphism (RFLP)-PCR method enabled the reliable discrimination between A2 (homozygote/heterozygote) and non-A2 animals. Since traces of β-casein A1 were also found in commercial "A2 milk" in Austria, the authentication of such expensive dairy products is urgently recommended, both by genotyping of all dairy cows at farm level (to confirm that all cows are homozygous β-casein A2A2) and by screening commercial products on the market (to confirm the absence of β-casein variants A1, B, and C in dairy products labelled "A2 milk") to protect consumers from this unexpected fraud.

Proteomic Advances in Milk and Dairy Products

Proteomics is a new area of study that in recent decades has provided great advances in the field of medicine. However, its enormous potential for the study of proteomes makes it also applicable to other areas of science. Milk is a highly heterogeneous and complex fluid, where there are numerous genetic variants and isoforms with post-translational modifications (PTMs). Due to the vast number of proteins and peptides existing in its matrix, proteomics is presented as a powerful tool for the characterization of milk samples and their products. The technology developed to date for the separation and characterization of the milk proteome, such as two-dimensional gel electrophoresis (2DE) technology and especially mass spectrometry (MS) have allowed an exhaustive characterization of the proteins and peptides present in milk and dairy products with enormous applications in the industry for the control of fundamental parameters, such as microbiological safety, the guarantee of authenticity, or the control of the transformations carried out, aimed to increase the quality of the final product.

Integrating genomic and infrared spectral data improves the prediction of milk protein composition in dairy cattle

Background

Over the past decade, Fourier transform infrared (FTIR) spectroscopy has been used to predict novel milk protein phenotypes. Genomic data might help predict these phenotypes when integrated with milk FTIR spectra. The objective of this study was to investigate prediction accuracy for milk protein phenotypes when heterogeneous on-farm, genomic, and pedigree data were integrated with the spectra. To this end, we used the records of 966 Italian Brown Swiss cows with milk FTIR spectra, on-farm information, medium-density genetic markers, and pedigree data. True and total whey protein, and five casein, and two whey protein traits were analyzed. Multiple kernel learning constructed from spectral and genomic (pedigree) relationship matrices and multilayer BayesB assigning separate priors for FTIR and markers were benchmarked against a baseline partial least squares (PLS) regression. Seven combinations of covariates were considered, and their predictive abilities were evaluated by repeated random sub-sampling and herd cross-validations (CV).

Results

Addition of the on-farm effects such as herd, days in milk, and parity to spectral data improved predictions as compared to those obtained using the spectra alone. Integrating genomics and/or the top three markers with a large effect further enhanced the predictions. Pedigree data also improved prediction, but to a lesser extent than genomic data. Multiple kernel learning and multilayer BayesB increased predictive performance, whereas PLS did not. Overall, multilayer BayesB provided better predictions than multiple kernel learning, and lower prediction performance was observed in herd CV compared to repeated random sub-sampling CV.

Conclusions

Integration of genomic information with milk FTIR spectral can enhance milk protein trait predictions by 25% and 7% on average for repeated random sub-sampling and herd CV, respectively. Multiple kernel learning and multilayer BayesB outperformed PLS when used to integrate heterogeneous data for phenotypic predictions.

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.

Impact of UHT treatment and storage on liquid infant formula: Complex structural changes uncovered by centrifugal field-flow fractionation with multi-angle light scattering

Protein modifications in liquid infant formula (IF) have been widely studied, but distinguishing between heat- and storage-induced structural changes remains challenging. A generic liquid IF was subjected to direct or indirect UHT treatment and stored at 40 °C up to 180 days. Colour and pH were monitored and structural changes were characterised by dynamic light scattering, SDS-PAGE and centrifugal field-flow fractionation (FFF) coupled with multi-angle light scattering (MALS) and UV detectors to evaluate whether heat-induced differences would level out during storage. Both direct- and indirect UHT treatment led to structural changes, where the higher heat load of the indirect UHT treatment caused more pronounced changes. Indications were that storage-induced changes in pH, browning and non-reducible cross-links were not dependent on UHT treatment. However, FFF-MALS-UV analysis allowed characterisation of complex aggregates, where structural changes continued to be most pronounced in indirect UHT treated samples, and different storage-induced aggregation behaviour was observed.

A rapid method to quantify casein in fluid milk by front-face fluorescence spectroscopy combined with chemometrics

Casein in fluid milk determines cheese yield and affects cheese quality. Traditional methods of measuring casein in milk involve lengthy sample preparations with labor-intensive nitrogen-based protein quantifications. The objective of this study was to quantify casein in fluid milk with different casein-to-crude-protein ratios using front-face fluorescence spectroscopy (FFFS) and chemometrics. We constructed calibration samples by mixing microfiltration and ultrafiltration retentate and permeate in different ratios to obtain different casein concentrations and casein-to-crude-protein ratios. We developed partial least squares regression and elastic net regression models for casein prediction in fluid milk using FFFS tryptophan emission spectra and reference casein contents. We used a set of 20 validation samples (including raw, skim, and ultrafiltered milk) to optimize and validate model performance. We externally tested another independent set of 20 test samples (including raw, skim, and ultrafiltered milk) by root mean square error of prediction (RMSEP), residual prediction deviation (RPD), and relative prediction error (RPE). The RMSEP for casein content quantification in raw, skim, and ultrafiltered milk ranged from 0.12 to 0.13%, and the RPD ranged from 3.2 to 3.4. The externally validated error of prediction was comparable to the existing rapid method and showed practical model performance for quality-control purposes. This FFFS-based method can be implemented as a routine quality-control tool in the dairy industry, providing rapid quantification of casein content in fluid milk intended for cheese manufacturing.

A label-free photoelectrochemical immunosensor for detection of the milk allergen β-lactoglobulin based on Ag2S -sensitized spindle-shaped BiVO4/BiOBr heterojunction by an in situ growth method

Food allergies have become a nonnegligible food safety issue, and milk allergies are one of the most common food allergies, that has attracted large consumer attention. In this work, a novel label-free photoelectrochemical (PEC) immunosensor for the detection of the allergen β-lactoglobulin (β-LG) in dairy products was designed that used the specific recognition of allergen β-LG and antibodies in dairy products in combination with biosensing technology. Here, Ag₂S-sensitized spindle-shaped BiVO₄/BiOBr heterojunction was fixed on the surface of the ITO electrode as an excellent photoactive substrate and effectively improved the photocurrent responses and sensitivity. Thioglycolic acid (TGA) was used as a linker to immobilize the β-LG antibody on the surface of the electrode. The photocurrent was detected at different antigen concentrations, which realized the quantitative testing of β-LG. Under the optimal experimental conditions, the PEC immunosensor proved an ideal linear relationship ranging from 10 pg/mL to 100 ng/mL, with a low detection limit of 3.7 pg/mL. The designed immunosensor showed good stability, a wide linear range, high sensitivity and good reproducibility and could be used for the detection of actual samples. The PEC immunosensor had a strong ability to specifically recognize β-LG, which was not affected by other proteins in the milk without pretreatment. Meanwhile, the developed immunosensor provided a promising PEC detection platform and reference idea for the detection of other proteins in milk.

Integration of Wet-Lab Measures, Milk Infrared Spectra, and Genomics to Improve Difficult-to-Measure Traits in Dairy Cattle Populations

The objective of this study was to evaluate the contribution of Fourier-transformed infrared spectroscopy (FTIR) data for dairy cattle breeding through two different approaches: (i) estimating the genetic parameters for 30 measured milk traits and their FTIR predictions and investigating the additive genetic correlation between them and (ii) evaluating the effectiveness of FTIR-derived phenotyping to replicate a candidate bull’s progeny testing or breeding value prediction at birth. Records were available from 1,123 cows phenotyped using gold standard laboratory methodologies (LAB data). This included phenotypes related to fine milk composition and milk technological characteristics, milk acidity, and milk protein fractions. The dataset used to generate FTIR predictions comprised 729,202 test-day records from 51,059 Brown Swiss cows (FIELD data). A first approach consisted of estimating genetic parameters for phenotypes available from LAB and FIELD datasets. To do so, a set of bivariate animal models were run, and genetic correlations between LAB and FIELD phenotypes were estimated using FIELD information obtained at the population level. Heritability estimates were generally higher for FIELD predictions than for the corresponding LAB measures. The additive genetic correlations (r_a) between LAB and FIELD phenotypes had different magnitudes across traits but were generally strong. Overall, these results demonstrated the potential of using FIELD information as indicator traits for the indirect genetic improvement of LAB measures. In the second approach, we included genotype information for 1,011 cows from the LAB dataset, 1,493 cows from the FIELD dataset, 181 sires with daughters in both LAB and FIELD datasets, and 540 sires with daughters in the FIELD dataset only. Predictions were obtained using the single-step GBLUP method. A four fold cross-validation was used to assess the predictive ability of the different models, assessed as the ability to predict masked LAB records from daughters of progeny testing bulls. The correlation between observed and predicted LAB measures in validation was averaged over the four training-validation sets. Different sets of phenotypic information were used sequentially in cross-validation schemes: (i) LAB cows from the training set; (ii) FIELD cows from the training set; and (iii) FIELD cows from the validation set. Models that included FIELD records showed an improvement for the majority of traits. This study suggests that breeding programs for difficult-to-measure traits could be implemented using FTIR information. While these programs should use progeny testing, acceptable values of accuracy can be achieved also for bulls without phenotyped progeny. Robust calibration equations are, deemed as essential.

Effects of High Intensity Ultrasound on Physiochemical and Structural Properties of Goat Milk β-Lactoglobulin

This study aimed to compare the effects of high intensity ultrasound (HIU) applied at various amplitudes (20~40%) and for different durations (1~10 min) on the physiochemical and structural properties of goat milk β-lactoglobulin. No significant change was observed in the protein electrophoretic patterns by sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE). Deconvolution and second derivative of the Fourier transform infrared spectra (FTIR) showed that the percentage of β-sheet of goat milk β-lactoglobulin was significantly decreased while those of α-helix and random coils increased after HIU treatment The surface hydrophobicity index and intrinsic fluorescence intensity of samples was enhanced and increased with increasing HIU amplitude or time. Differential scanning calorimetry (DSC) results exhibited that HIU treatments improved the thermal stability of goat milk β-lactoglobulin. Transmission electron microscopy (TEM) of samples showed that the goat milk β-lactoglobulin microstructure had changed and it contained larger aggregates when compared with the untreated goat milk β-lactoglobulin sample. Data suggested that HIU treatments resulted in secondary and tertiary structural changes of goat milk β-lactoglobulin and improved its thermal stability.