Symposium review: Characterization of the bovine milk protein profile using proteomic techniques

The skimmed milk proteome of dairy cows is affected by the stage of lactation and by supplementation with polyunsaturated fatty acids

The impact of nutritional modification to increase functional polyunsaturated fatty acids (PUFA), such as n-3 and n-6 fatty acids (FA) or conjugated linoleic acid (CLA), on milk proteome profile during early lactation remains largely unknown. We used an untargeted proteomics approach to investigate the impact of lactation day and PUFA supplementation on the proteome signature in skimmed milk over the course of early lactation. Sixteen Holstein dairy cows received abomasal infusion of saturated FA (CTRL) or a mixture of essential FA and CLA (EFA + CLA group) from - 63 to + 63 days relative to parturition. Using quantitative proteomics, 479 unique proteins were identified in skimmed milk at days 1, 28, and 63 postpartum. The top discriminating proteins between transition milk (day 1) and mature milk (days 28 and 63), including members of complements (i.e. C2 and C5), growth factor (TGFB2), lipoproteins (i.e. APOE and APOD), and chaperones (i.e. ST13 and CLU), are associated with calves' immune system and gut development. The EFA + CLA supplementation moderately affected a few proteins associated with regulating mammary glands' lipogenesis through the (re)assembly of lipoprotein particles, possibly under the PPAR signaling pathway. Collectively, skimmed milk proteome is dynamically regulated initially by cow's metabolic and physiological changes and to a lesser extent by nutritional PUFA modifications.

The Characterization of a Low-Calorie and Lactose-Free Brown Fermented Milk by the Hydrolysis of Different Enzymatic Lactose

The adoption of brown fermented milk in the normal diet and daily beverages is accompanied by significant sugar intake and a high public health burden. To reduce the sugar content in dairy products while maintaining optimal nutritional properties, a novel low-calorie, lactose-free brown fermented milk was developed through enzymatic hydrolysis and the Maillard reaction. The optimal product was achieved using low-temperature lactase, where the lactose and glucose content were reduced 33-fold and 2.4-fold to 0.06 g/100 g and 13.32 g/L, respectively, meeting the criteria for being lactose-free (<0.5 g/100 g). Meanwhile, hazardous compounds such as 5-hydroxymethylfurfural and 3-deoxyglucosone were reduced by more than 20%. After 28 days of storage, the water-holding capacity and suspension stability remained notably stable, and the protein composition was also more enriched compared to commercial milk. It is expected that this low-calorie dairy product may promote growth in the dairy market.

Bioactivity and volatile compound evaluation in sheep milk processed by ohmic heating

Ohmic heating may improve bioactive compounds and processing, ensuring food safety of beverages, liquid and pasty food, or liquid with solid pieces. Due to those traits, this study conducted a comparison between ohmic heating technology and conventional heating (CH), with a focus on assessing the impact of both methods on functional compounds (such as angiotensin-converting enzyme inhibition, α-amylase and α-glucosidase inhibition, and antioxidant activity) in both fresh and thawed raw sheep milk, which had been frozen for up to 3 mo. Different ohmic heating conditions were applied and compared to CH (3.33-8.33 V/cm vs. CH [73°C/15 s]). A total of 18 peptides with some functional activities were identified by MALDI-TOF mass spectrometry analysis. Ohmic heating samples presented the highest activities related to health, followed by CH and raw milk samples; antioxidant activity range was from 0.11% to 0.71%, antihypertensive activity ranged from 0.20% to 0.72%, and antidiabetic activity ranged from 0.21% to 0.79%. Of 51 volatile compounds detected, some were degraded by freezing, storing, and heating the sheep milk. This study showed for the first time that ohmic heating processing improved sheep milk bioactive peptides and preserved volatile compounds.

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.

A novel strategy to construct stable fat globules with all major milk fat globule membrane proteins to mimic breast milk fat emulsions at the protein level

Milk fat globule membrane (MFGM) proteins have several biological functions and maintain the fat globule structure. However, the major MFGM protein compositions in simulated human milk emulsions are different from those in human milk due to the composition loss in the isolation process of MFGM materials. To overcome this limitation, we developed a novel strategy, namely, the solution enriched with MFGM was homogenized with cream separated from the milk rich in large-sized fat globules. The results of physicochemical properties and the interfacial protein coverage of the emulsions showed that the emulsions prepared by the new method had a smaller particle size, higher stability, and more interfacial protein coverage when the ratio of fat to protein was 1:3. In addition, proteome differences in interfacial proteins between the new emulsions and simulated infant formula emulsions were investigated, and the results revealed that the interface of the emulsions prepared by the new method contained all major MFGM proteins and unique GO annotations and KEGG pathways. However, only four MFGM proteins (XO, ADPH, PAS 6/7) were quantified at the interface of the emulsions prepared by the common method. Furthermore, the protein number and the total relative abundance of major MFGM proteins were approximately 2-fold and 475-fold higher at the interface of the emulsions prepared by the new method compared to the common method. Overall, the study modulated the interfacial protein composition of fat globules by screening the sources of lipid and homogenization methods and revealed its potential effect on processing stability and biological properties.

The Promise and Challenges of Determining Recombinant Bovine Growth Hormone in Milk

Recombinant bovine growth hormone (rbGH) is produced in large quantities and widely used in a number of countries worldwide to stimulate milk production in dairy animals. The use of this compound in animal production is strictly regulated by food safety directives in force, in particular in the European Union (EU). Although analytical strategies for the detection of rbGH in blood have been successfully reported over the past 15 years, they do not fully answer the expectations of either competent authorities or industrials that would expect measuring its occurrence directly in the milk. As a matrix of excretion but also of consumption, milk appears indeed as the matrix of choice for detecting the use of rbGH in dairy animals. It also allows large volumes to be collected without presenting an invasive character for the animal. However, rbGH detection in milk presents several challenges, mainly related to the sensitivity required for its detection in a complex biological matrix. This review article presents the specific difficulties associated with milk and provides an overview of the analytical strategies reported in the literature and whether they concern indirect or direct approaches to the detection of rbGH administration to animals, with applications either for screening or confirmation purposes.

Cardiometabolic health benefits of dairy-milk polar lipids

Low-quality dietary patterns impair cardiometabolic health by increasing the risk of obesity-related disorders. Cardiometabolic risk relative to dairy-food consumption continues to be a controversial topic, due to recommendations that endorse low-fat and nonfat dairy foods over full-fat varieties despite accumulated evidence that does not strongly support these recommendations. Controlled human studies and mechanistic preclinical investigations support that full-fat dairy foods decrease cardiometabolic risk by promoting gut health, reducing inflammation, and managing dyslipidemia. These gut- and systemic-level cardiometabolic benefits are attributed, at least in part, to milk polar lipids (MPLs) derived from the phospholipid- and sphingolipid-rich milk fat globule membrane that is of higher abundance in full-fat dairy milk. The controversy surrounding full-fat dairy food consumption is discussed in this review relative to cardiometabolic health and MPL bioactivities that alleviate dyslipidemia, shift gut microbiota composition, and reduce inflammation. This summary, therefore, is expected to advance the understanding of full-fat dairy foods through their MPLs and the need for translational research to establish evidence-based dietary recommendations.

Comparative proteomic characterization of bovine milk containing β-casein variants A1A1 and A2A2, and their heterozygote A1A2

BACKGROUND

Genetic variants of β-casein are cosnidered to affect the components of milk. However, limited data are available on the bovine protein components correlated with β-casein variants at the proteome level. In the present study, cows producing milk containing β-casein variants (A1A1 and A2A2) and their heterozygote (A1A2) were identified using a high-resolution melting method, and milk samples were collected and tested. Comparative analyses of casein micelles, whey and milk fat globule membrane fractions in each milk variant were performed using a label-free proteomics approach.

RESULTS

The results obtained showed that ceruloplasmin and cathelicidin-2 were the most abundant proteins in milk containing variant A1A1; lactoferrin and CD5 molecule-like were the most abundant proteins in milk containing variant A2A2; and selenoprotein P and osteopontin were the most abundant proteins in milk containing heterozygote A1A2. Differences in protein components in milk containing the different β-casein variants were visualized using hierarchical clustering, and profiles were separated using principal components analysis. The differentially expressed proteins in milk containing A1A1, A2A2 or A1A2 were predominantly involved in response to stress and defense response according to their Gene Ontology annotations.

CONCLUSION

Our findings provide new insights into differentially expressed milk proteins corresponding to the presence of different β-casein variants. This knowledge will help determine their potential biological functions in dairy products and the effects on human health. © 2020 Society of Chemical Industry.

Use of a magnetic covalent organic framework material with a large specific surface area as an effective adsorbent for the extraction and determination of six fluoroquinolone antibiotics by HPLC in milk sample

A magnetic covalent organic framework material was synthesized with a core-shell structure using a simple solvothermal method. It was prepared with Fe₃ O₄ as the magnetic core, covalent organic framework as the shell, which synthesized from 1,3,5-triformylphloroglucinol and p-phenylenediamine by Schiff base reaction. Transmission electron microscopy, Fourier transform infrared spectroscopy, powder X-ray diffraction, vibrating sample magnetometry, and nitrogen adsorption-desorption were used to characterize magnetic adsorbent. It has showed a large specific surface area (505.6 m² /g), which can provide many adsorption sites. Moreover, the saturation magnetization value was 48.4 emu/g enough to be separated by external magnet. Six kinds of fluoroquinolones (enoxacin, fleroxacin, ofloxacin, norfloxacin, pefloxacin, and lomefloxacin) were extracted by magnetic solid phase extraction with the magnetic adsorbent. High-performance liquid chromatography detects the entire adsorption and desorption process to further evaluate the optimal extraction and desorption conditions. Under the optimal chromatographic conditions, this method showed a low detection limit (0.05 to 0.20 μg/L), good linearity in the range of 0.5 to 200 μg/L, and the enrichment factor reaches 115.5-127.3. The spiked recovery of the fluoroquinolones in milk sample ranged from 90.4 to 101.2%.

Shifts in the Holstein dairy cow milk fat globule membrane proteome that occur during the first week of lactation are affected by parity

Background

The milk fat globule membrane (MFGM) proteomes of colostrum and transition milk are rich sources of proteins that are likely important for neonatal calf health. In addition, characterization of these proteomes could also yield valuable information regarding mammary gland physiology of the early postpartum lactating cow. The objectives of this research were to characterize the MFGM proteomes of colostrum and transition milk through sample collections at four timepoints postpartum, including the first milking (M1, colostrum), second milking (M2, transition milk), fourth milking (M4, transition milk), and fourteenth milking (M14, mature milk), and compare these proteomes between multiparous (MP; n = 10) and primiparous (PP; n = 10) Holstein dairy cows. Isolated MFGM proteins were labeled using Tandem Mass tagging and analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Protein identification was completed using MASCOT and Sequest in Proteome Discoverer 2.2. The scaled abundance values were analyzed using PROC MIXED in SAS to determine the effects of milking (MIL), parity (PAR), and MIL × PAR. The adaptive false-discovery rate (FDR)-adjusted P values were determined using PROC MULTTEST. Protein characterization and bioinformatic analysis were completed using a combination of PANTHER, Blast, and Uniprot.

Results

A total of 104 common proteins were identified in each of the MFGM samples. Statistical analysis revealed that 70.2% of identified proteins were affected by MIL. Of these, 78.1% were lower in M14 compared with M1, including immune-related proteins lactotransferrin, lactadherin and hemopexin. Parity affected 44.2% of proteins. Of the proteins affected by PAR, 84.8% were higher in MP cows compared with PP cows, including apolipoprotein E and histones 2A, 2B, 3, and 4 b. Butyrophilin subfamily 1 member 1A and annexin 5 were higher in samples from PP cows. Milking × parity affected 32.7% of identified proteins, including lactotransferrin, gelsolin, vitamin D binding protein, and S100 proteins.

Conclusions

This research supports previous findings that the Holstein MFGM proteome changes rapidly during the first week of lactation. In addition, this research identifies the impact of parity on the colostrum and transition milk MFGM proteomes, which may be important for milk-fed calf health or for the identification of protein biomarkers for mammary functionality.

Comparative analysis of the skim milk and milk fat globule membrane proteomes produced by Jersey cows grazing pastures with different plant species diversity

The objective of this experiment was to identify and characterize the bovine milk proteome within the skim milk fraction and milk fat globule membrane (MFGM)-associated fraction from 16 organically certified lactating Jersey cows after a short term of grazing pastures with or without annual forage crops (AFC). Cows were offered a partial mixed ration (~60% of dry matter intake) and approximately 40% of their total dry matter intake as herbage. Eight cows were offered a cool-season grass–legume herbage (GLH), which included orchardgrass (Dactylis glomerata), timothy (Phleum pratense), Kentucky bluegrass (Poa pratensis), and white clover (Trifolium repens). The other 8 cows were offered the same GLH strip-tilled with the AFC, including oat (Avena sativa), millet (Pennisetum glaucum), teff (Eragrostis tef), buckwheat (Fagopyrum esculentum), and chickling vetch (Lathyrus sativus). Milk samples were collected from each cow during a.m. and p.m. milkings on d 19 to 21 of grazing, and composite milk samples per cow were analyzed for (1) the high-abundance milk protein profile, (2) the skim milk low-abundance protein-enriched proteome, and (3) the MFGM proteome. Of the 443 proteins identified in the skim and MFGM proteomes, 433 were included in statistical analysis, including 68 proteins identified in the skim milk fraction and 365 in the MFGM-associated fraction. Analysis of the skim and MFGM proteomes encompassed unique gene ontology profiles and proportions of functional classifications. In response to diet, α_S1-casein as well as 8 low-abundance proteins were present in higher concentration or abundance in milk from cows grazing the GLH strip-tilled with the AFC compared with milk from cows grazing GLH, suggesting that even short-term grazing of pastures including some AFC may affect the milk proteome.

Inclusion of grape marc in dairy cattle rations alters the bovine milk proteome

Grape marc (GPM) is a viticulture by-product that is rich in secondary compounds, including condensed tannins (CT), and is used as a supplement in livestock feeding practices. The aim of this study was to determine whether feeding GPM to lactating dairy cows would alter the milk proteome through changes in nitrogen (N) partitioning. Ten lactating Holstein cows were fed a total mixed ration (TMR) top-dressed with either 1.5 kg dry matter (DM)/cow/day GPM (GPM group; n = 5) or 2.0 kg DM/cow/day of a 50:50 beet pulp: soy hulls mix (control group; n = 5). Characterization of N partitioning and calculation of N partitioning was completed through analysis of plasma urea-N, urine, feces, and milk urea-N. Milk samples were collected for general composition analysis, HPLC quantification of the high abundance milk proteins (including casein isoforms, α-lactalbumin, and β-lactoglobulin) and liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis of the low abundance protein enriched milk fraction. No differences in DMI, N parameters, or calculated N partitioning were observed across treatments. Dietary treatment did not affect milk yield, milk protein or fat content or yield, or the concentrations of high abundance milk proteins quantified by HPLC analysis. Of the 127 milk proteins that were identified by LC-MS/MS analysis, 16 were affected by treatment, including plasma proteins and proteins associated with the blood-milk barrier, suggesting changes in mammary passage. Immunomodulatory proteins, including butyrophilin subfamily 1 member 1A and serum amyloid A protein, were higher in milk from GPM-fed cows. Heightened abundance of bioactive proteins in milk caused by dietary-induced shifts in mammary passage could be a feasible method to enhance the healthfulness of milk for both the milk-fed calf and human consumer. Additionally, the proteome shifts observed in this trial could provide a starting point for the identification of biomarkers suitable for use as indicators of mammary function.

Classifying the fertility of dairy cows using milk mid-infrared spectroscopy

The objective of this study was to investigate the potential of milk mid-infrared (MIR) spectroscopy, MIR-derived traits including milk composition, milk fatty acids, and blood metabolic profiles (fatty acids, β-hydroxybutyrate, and urea), and other on-farm data for discriminating cows of good versus poor likelihood of conception to first insemination (i.e., pregnant vs. open). A total of 6,488 spectral and milk production records of 2,987 cows from 19 commercial dairy herds across 3 Australian states were used. Seven models, comprising different explanatory variables, were examined. Model 1 included milk production; concentrations of fat, protein, and lactose; somatic cell count; age at calving; days in milk at herd test; and days from calving to insemination. Model 2 included, in addition to the variables in model 1, milk fatty acids and blood metabolic profiles. The MIR spectrum collected before first insemination was added to model 2 to form model 3. Fat, protein, and lactose percentages, milk fatty acids, and blood metabolic profiles were removed from model 3 to create model 4. Model 5 and model 6 comprised model 4 and either fertility genomic estimated breeding value or principal components obtained from a genomic relationship matrix derived using animal genotypes, respectively. In model 7, all previously described sources of information, but not MIR-derived traits, were used. The models were developed using partial least squares discriminant analysis. The performance of each model was evaluated in 2 ways: 10-fold random cross-validation and herd-by-herd external validation. The accuracy measures were sensitivity (i.e., the proportion of pregnant cows that were correctly classified), specificity (i.e., the proportion of open cows that were correctly classified), and area under the curve (AUC) for the receiver operating curve. The results showed that in all models, prediction accuracy obtained through 10-fold random cross-validation was higher than that of herd-by-herd external validation, with the difference in AUC ranging between 0.01 and 0.09. In the herd-by-herd external validation, using basic on-farm information (model 1) was not sufficient to classify good- and poor-fertility cows; the sensitivity, specificity, and AUC were around 0.66. Compared with model 1, adding milk fatty acids and blood metabolic profiles (model 2) increased the sensitivity, specificity, and AUC by 0.01, 0.02, and 0.02 unit, respectively (i.e., 0.65, 0.63, and 0.678). Incorporating MIR spectra into model 2 resulted in sensitivity, specificity, and AUC values of 0.73, 0.63, and 0.72, respectively (model 3). The comparable prediction accuracies observed for models 3 and 4 mean that useful information from MIR-derived traits is already included in the spectra. Adding the fertility genomic estimated breeding value and animal genotypes (model 7) produced the highest prediction accuracy, with sensitivity, specificity, and AUC values of 0.75, 0.66, and 0.75, respectively. However, removing either the fertility estimated breeding value or animal genotype from model 7 resulted in a reduction of the prediction accuracy of only 0.01 and 0.02, respectively. In conclusion, this study indicates that MIR and other on-farm data could be used to classify cows of good and poor likelihood of conception with promising accuracy.

Milk proteome from in silico data aggregation allows the identification of putative biomarkers of negative energy balance in dairy cows

A better knowledge of the bovine milk proteome and its main drivers is a prerequisite for the modulation of bioactive proteins in milk for human nutrition, as well as for the discovery of biomarkers that are useful in husbandry and veterinary medicine. Milk composition is affected by lactation stage and reflects, in part, the energy balance of dairy cows. We aggregated the cow milk proteins reported in 20 recent proteomics publications to produce an atlas of 4654 unique proteins. A multistep assessment was applied to the milk proteome datasets according to lactation stages and milk fractions, including annotations, pathway analysis and literature mining. Fifty-nine proteins were exclusively detected in milk from early lactation. Among them, we propose six milk proteins as putative biomarkers of negative energy balance based on their implication in metabolic adaptative pathways. These proteins are PCK2, which is a gluconeogenic enzyme; ACAT1 and IVD, which are involved in ketone metabolism; SDHA and UQCRC1, which are related to mitochondrial oxidative metabolism; and LRRC59, which is linked to mammary gland cell proliferation. The cellular origin of these proteins warrants more in-depth research but may constitute part of a molecular signature for metabolic adaptations typical of early lactation.