Open access peer-reviewed chapter - ONLINE FIRST

Omics, the New Technological Approaches to the Milk Protein Researches

Written By

Zitai Guo, Lu Ma and Dengpan Bu

Submitted: December 24th, 2021 Reviewed: January 5th, 2022 Published: April 7th, 2022

DOI: 10.5772/intechopen.102490

IntechOpen
Milk Protein - New Research Approaches Edited by Narongsak Chaiyabutr

From the Edited Volume

Milk Protein - New Research Approaches [Working Title]

Prof. Narongsak Chaiyabutr

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Abstract

With the development of technological approaches, the perturbations of biological information in gene, mRNA, proteins, and metabolites have been gathered to broaden the cognition of synthesis processes during lactation. While omics, the series of application including genomics, transcriptomics, proteomics, and metabolomics, are mostly preferred and conducted in the investigation of lactation especially the milk protein. These new technological approaches provide a complete view of the molecular regulation pathways and make it possible to systematically investigate the lactation. The aim of this chapter is to comprehensively review the advances in knowledge regarding the great progress in milk protein synthesis as well as lactation physiology and pathology mainly in dairy cows obtained from omics technologies, meanwhile the milk proteins as well as their attributes are illustrated.

Keywords

  • milk protein
  • omics technologies
  • dairy cows
  • protein synthesis

1. Introduction

Milk protein is one of the most important nutrients in milk. It contains a variety of essential amino acids required by body maintaining and is believed to have a variety of potential biological functions [1, 2]. In past few decades, plenty of research studies were conducted for improving the milk quality especially the milk protein production, while the morphological as well as physiological focused on mammary gland has been widely investigate [3, 4, 5, 6]. However, since the synthesis of milk protein during lactation is a complex biological activity, only little perturbations in lactation can result in a certain difference in the composition and concentration of milk protein [7]. Furthermore, the interactions between proteins, genes, and factors are diversity and dynamics when performing physiological functions, which means the tradition approaches may no longer meet the requirement of current research studies. In recent years, new approaches including Omics in lactation-related research studies received extensive attention. While Omics was one of the most used approaches since it make the study possible to explain the synthesis comprehensively and systematically at the levels of DNA, RNA, proteins, and metabolites, which can assist the further indentation of factors as well as processes regulating lactation [8, 9]. To present the use of omics approach in lactation especially milk protein synthesis research in dairy cows, the relevant introductions of omics and milk protein following the great progress in lactation physiology as well as pathology by these new approaches are illustrated in the current chapter.

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2. Milk protein and its attributes

Suppose milk was considered an important nutrient source due to its perspective of molecular composition, milk proteins should be the most important source of bioactive peptides. Milk proteins were proved to have higher digestibility and more suitable content of amino acids for human being [10], which contribute to more than 3% of content in milk [11]. Based on the properties of structure, function, and solubility, milk proteins are normally divided into three categories including caseins, whey proteins, and milk fat globular membrane proteins, while these complex components make the milk proteins to vary widely [12, 13]. In short, caseins account for about 80% of total milk proteins and were mainly classified by four basic types of molecules: the αs1-, αs2-, β-, and κ-caseins [14, 15]. Whey proteins are the major component of milk whey, their components mainly include β-lactoglobulin (β-LG), α-lactalbumin (α-LA), serum albumin (SA), immunoglobulin G (IgG), and also include several small molecule proteins especially low-abundance proteins, such as enzymes and metal-binding proteins [16]. Milk fat globular membrane proteins only contribute to 1–4% of milk proteins, but play the important roles in the defense mechanisms and process of cell growth in newborns [17]. So far, plenty of research studies have investigated the types, structures as well as synthesis of those components in milk proteins, which would be reviewed in later paragraphs.

2.1 Caseins

Casein is a kind of phosphorous-containing protein [18]. The serine hydroxyl group inside casein forms an ester bond to the phosphate group, which gives it the common feature of amphiphilic. Caseins classified by different types may contain different amount of phosphate groups [19]. However, all kinds of caseins keep at least one phosphate with ester bonded. Since the caseins contain amount of phosphorylated serine groups, which bind in the form of covalent bonds [20], these groups keep the form of clusters on the surface of molecules and provide conditions for its binding to calcium ions [21], which was considered to be the most important nutritional function of casein.

The αs1-, αs2-, β-, and κ-caseins are four basic types of casein molecules as mentioned above, which are also the types synthesized by the mammary gland of dairy cows. Except for major installations, there are numerous minor fractions of caseins such as γ-casein. While none of those were found in the composition of milk [22]. Though the amino acid sequence, number, and total charge of casein are not completely the same among different variant individuals, the composition of amino acids still has the following features [23, 24, 25]:

  1. The amino acids with polar and nonpolar are unevenly distributed, forming obvious hydrophilic and hydrophobic regions.

  2. The content of nonpolar amino acids is higher than those with polar, while the amounts of proline and lysine are higher as well.

  3. The content of sulfur-containing amino acids is lower than normal.

Though the synthesis of milk protein is closely related to animal science, the research on its structures was mostly investigated in field of food science. For caseins, the research on those monomers has become the hotspot in recent years. Previous study has predicted the structure of αs-casein by molecular simulation, and its quaternary structures of caseins were investigated by Fourier transform infrared spectroscopy as well [26]. Specifically, αs1-casein has the ability of self- aggregation, but is affected by factors including condition pH as well as the ionic strength [27]. The increase of pH value will weaken its self-aggregation, to the opposite, the increase of ionic strength will enhance self-aggregation [28]. The ability of self-aggregation in αs2-casein is similar to that in αs1-casein, which mostly depends on the ionic strength, but the aggregation begins to be weakened once the strength arrives at 0.2 mol/L [29].

The research related to the structures of β-casein is contradicted and still unclear. Noelken et al. firstly predicted the form of β-casein in random coils in aqueous solution with only a small amount of regular structure [30], However, the results cannot be consistent due to the difference in temperature, ionic strength, protein concentration, etc., and these factors all contribute to affecting the ability of its self-aggregation [31]. β-casein exists as a monomer at low temperature and begins to aggregate as the temperature rises. While self-aggregation gradually increased and reached the maximum, once the protein concentration surpasses the threshold [32]. However, the effect of pH on the self-aggregation ability of β-casein is still inconclusive.

κ-casein is located on the surface of the casein micelle structure. Its most important role is to maintain the stability of the micelle structure and act as transition in the hydrophobic casein and water [33]. The unique disulfide bonds give κ-casein special properties different from the rest three types [34]. Though the self-aggregation of κ-casein consists of a core surrounded by multiple layers of variable polypeptide regions [35], which is similar to that of β-casein, it’s not affected by temperature and ionic strength within a certain range and forms a fixed-size polymer.

In addition to nutritional functions, the potential biological activity of peptides formed as a result of casein proteolysis in the gastroenteric tract has been widely valued [36]. These peptides may affect the cardiovascular, nervous, immune, and digestive systems [37, 38]. However, it has been established that peptides are distributed unevenly in the composition of primary structure of caseins, which has attracted more attention to related research studies.

2.2 Whey proteins

Whey is a by-product during casein production, it can remain the form of liquid after coagulation by rennet, while the proteins left are the whey proteins [39]. Whey proteins are in full value and contain all kinds of amino acids that make up proteins [40]. And except for a little bit lower content in sulfur-containing amino acids, whey proteins have higher contents of the rest of essential amino acids compared with other proteins [41]. Therefore, whey contributes to nearly half of the nutrients in milk even though its total solids are only around 6.0 ~ 6.5% [16]. The high quality of whey proteins with complete and appropriate proportion of essential amino acids meets the requirement of human being, which also determines the functions of whey proteins. As mentioned above, whey proteins consist of a variety of biologically active ingredients including β-lactoglobulin, α-lactalbumin, serum albumin, immunoglobulin, and a variety of growth factors and biologically active peptides.

It’s clear that the composition of amino acids determines the biological activity of each component in whey proteins. The various amino acids including threonine, cysteine, methionine are important to the intestine, muscle, and antioxidant systems [42]. While the physiological functions of whey proteins as well as the main amino acid related are reviewed below.

The β-lactoglobulin is the most prevalent one and comprises more than half of the whole proteins, while its prevalence affects the attributes of whey, β-lactoglobulin contains 162 amino acids with two variants differ in one amino acid, the disulfide and free sulfhydryl groups in its molecules forms let it become the major source of sulfur-contained amino acid [43]. β-lactoglobulin is manufactured in the ruminants while almost all of non-ruminants cannot synthesis it in the mammary gland [44]. The hydrophobic area on molecule of β-lactoglobulin is a quite effective in binding retinol, which may contribute to regulating the mammary gland by vitamin A [45]. However, the related biological functions of β-lactoglobulin are not commonly accepted now.

α-lactalbumin comprises around 13% of the whole whey proteins, with four disulfide linkages and no phosphate group molecule. The function of modifying the activity of the enzyme galactosyl transferase was proved in former studies, which promoting the transfer of UDP galactose to glucose [46]. α-lactalbumin is closely related to lysozyme evidenced by the similar synthesize of linkage but does not work on the same substrates, nor antigenically [47]. In addition, the α-lactalbumin is more heat-stable in the presence of calcium rather than in the absence of calcium [48], which is unusual compared with other proteins.

Different from the former two components, the serum albumin and immunoglobulins are not synthesized in the mammary gland. The serum albumins isolated from milk have the same molecule to those serum proteins since they are leaked into milk from the bloodstreams [49]. Therefore, serum albumins are identical to be the same molecule with serum proteins. Serum albumins contain no phosphorous with only one free sulfhydryl group, which gives those a specific binding sites for hydrophobic [50]. While the immunoglobulins in milk proteins comprise more than 2% of the total content and are classified by four types including IgG1, IgG2, IgA, and IgM. Immunoglobulins in colostrum can provide the passive immunity to the calf until the synthesis of antibodies activates in their body [51].

2.3 Milk fat globular membrane proteins

Milk fat globule membrane (MFGM) is the layer of film wrapped on the surface of milk fat, the function of which is to protect fat globule from polymerization or enzymatic degradation [52]. Milk fat globular membrane proteins (MFGMPs) are protein component in MFGM and contribute to the 25% ~ 70% of total contents [53]. MFGMPs have the most diverse biological functions and play an important role in the cell growth process and defense functions of newborns [54, 55].

The three-layer structure theory of milk fat globule membrane has been widely accepted [56]. While the main components of MFGMs including xanthine oxidoreductase, butyrophilin, and lactadherin play the most important role [57]. The innermost layer of the milk fat globule membrane is a single-layer membrane composed of polar lipids and proteins synthesized by the endoplasmic reticulum, which wraps the fat droplets in the core of the fat globule, followed by a high-density protein layer attached to the inner surface of the double-layer membrane; The last is the lipid bilayer that comes from the apical membrane of breast epithelial cells [58]. The cytoplasm forms a cytoplasmic crescent between the high-density protein layer and the outer double-membrane layer.

Xanthine oxidoreductase (XO/XDH) is the main component of milk fat globular membrane protein. It has been confirmed that it has a certain role in breast development, intestinal antibacterial and tissue damage [59]. XO/XDH is a member of the flavoprotein family of molybdenum dehydrogenase, which is a key enzyme for purine metabolism in the organism. However, the role of XO/XDH in the process of milk fat droplet wrapping and secretion may not express enzymes [60]. In addition, xanthine oxidoreductase has been confirmed to have a certain role in mammary gland development, intestinal antibacterial and tissue damage [61].

Butyrophilins (BTNs) are proteins related to fat droplets and a member of the immunoglobulin family. Many members of the BTN family have been confirmed to have immunomodulatory effects [62]. For example, the BTN3A1 and BTN3 families can inhibit T cell activation [63]. Milk-derived BTN has cross-reactivity with specific neuronal antibodies, which may be related to autoimmune regulation of diseases such as autism and multiple sclerosis [64].

Lactadherins are immunogenic lipophilic glycoproteins and are also known as milk fat globule epidermal growth factor 8 [65]. They are mainly distributed in secretory cells at the top of the milk tubules. In recent years, research on MFG-E8 has mainly focused on the phagocytosis of apoptotic cells, immune regulation, coagulation, and thrombosis [66]. Nakatani et al. found that MFG-E8 can recognize apoptotic cells in breast recession and activate phagocytes to phagocytose apoptotic epithelial cells. MFG-E8 can also resist rotavirus infection [67]. The protective effect of MFG-E8 on the intestinal tract has also become a research hotspot, which is mainly reflected in its anti-inflammatory, anti-apoptotic, and promoting intestinal mucosal repair effects [68].

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3. Omics, a series of novel approaches to study milk protein

With the advent of the post-genomic era, the interactions between proteins, genes, and factors are followed by researchers, the diversity and dynamics of physiological functions cause the tradition approaches unable meet the requirement of current research studies. In recent years, a large number of research approaches including Omics have emerged in the research fields of biology [69, 70]. The emergence of these new applications can provide a complete view of the molecular regulation pathways of cells and organisms and make it possible to systematically investigate the lactation at the levels of genes, proteins, and even the metabolites, which is much helpful for the investigation of lactation especially the milk protein.

Omics are series of applications including genomics, transcriptomics, proteomics, and metabolomics in biological research. Genomics focus on the heterogeneity of coding genes, to investigate the sequence and expression of DNA, it provides the insight into the genetic structures by mapping as well as the performing the sequence analysis [71]. Transcriptomics profile the expression of mRNA in cells at specific time or state, while it can simultaneously work on more than thousands of changes in mRNA expression. Proteomics are used to determine the perturbations of expression patterns, abundance, and posttranslational modifications in proteins, and specialized in the differences caused by these factors [72]. While metabolomics monitor the changes in large groups of metabolites in biological samples, during which the further integration is conducted to reflect the physicochemical properties [73]. By applying these new approaches, the knowledge related to dairy science especially milk synthesis has been pushed forward tremendously in recent years, meanwhile the determination and analysis methods applied were developing as well, which were specifically overviewed in later section.

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4. Genomics in milk protein research

Genomics involves genome mapping by genetic, physical, and transcript, gene sequence analysis and gene functional analysis, and was used in breeding selection. Since the DNA sequencing as well as high -density microarray analysis (gene chips) was commonly used in inferring genomics, the widespread of new next sequencing technology pushes the application of these two technologies in genomic studies related to lactation [74]. To improve the performance, dairy cows were already fully sequenced, and former studies of genomics in lactation research studies focused on the nutritional strategies and specific genes linked to the milk quality. However, the available data of genomics research on milk protein synthesis were still scarce in recent years. Since most of related studies concern more on the association of milk proteins with milk production traits instead of milk proteins variants with milk proteins composition [75]. The applications of genomics are mainly focused on the strong candidate of QTL, the variants of milk proteins, and the diseases that may affect the milk protein synthesis (i.e., Mastitis) [76]. Here we summarized those from mapping approaches to genome-wide association studies.

Lactation is usually affected by the factors such as environment, nutritional manages, breed, etc. The combination of the genetic data with the nutrition management including dry matter intake, body condition (in different periods) contributes to the efficient prediction of traits related to lactation as well as milk protein synthesis [77]. Former studies focused on the detection of relationships between lactation and the candidate genes related to milk proteins. And it has been shown that genes on chromosome 3 of bovine including the insulin-like growth factor 2 (IGF-2) and rap-1A are the strong candidate for the quantitative trait locus (QTL) and may affect the milk performance [78, 79], IGF-2 was found to have the functions of muscle mass and fat deposition in swine and was widely investigated in human medical. A parametric bootstrapping procedure found by Veerkamp et al. makes the estimate of heritability and genetic correlations between traits possible [80]. In addition, the development of genome-wide analysis makes it become a better solution to explain key genes and pathways. Berkowicz et al. indicated that a single genotyped single-nucleotide polymorphism (SNP) and traits related to animal growth also support the locus as harboring a potentially important quantitative trait nucleotides (QTNs) [79], suggesting that reprinter genes together with those documented biological roles represent important reservoirs for genetic improvement of dairy cows.

The genomics studies of milk proteins mainly focus on the amino acid changes caused by polymorphisms in the corresponding genes, while previous research studies focus on the variants on the components of caseins as well as whey proteins. To be specific, the A and B variants of β-LG and κ-CN on their concentration and total proteins in milk, which indicated that the A variant of β-LG is associated with a greater concentration of β-LG and a lesser concentration of casein, and that the B variant of κ-CN is associated with a greater concentration of κ-CN in milk [81]. But the research on the genotypes of all major components in milk proteins was not widely investigated in different kinds of animals. While in dairy cows, the A and B variants of β-LG and κ-CN, the E variant of κ-CN, and the A1, A2, and B variants of β-CN frequently occurred [82]. The genes of four different caseins have been found to be located at chromosome 6 of bovine and are closely linked meanwhile organized in a casein locus [83]. Heck et al. indicated that the 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 production [84]. While related studies have also found the specific genes linked to milk proteins synthesis were also affected by the factors including seasons, lactation stages [81]. Therefore, the advance investigation of genes as well as variants will greatly enable the assessment of breeding to milk protein composition.

Mastitis is the most common disease in dairy cows, which is hallmarked by high somatic cell count (SCC). Mastitis negatively affects the dairy industry and enormously causes losses in milk performance and management costs [85]. Related research studies have shown that the stromal fibroblasts derived from cows that suffered mastitis were upregulated in the expression of inflammatory-related cytokines TNF-α and IL-8 [86], which contribute to the inhabitation the synthesis of milk proteins components including β-casein. Therefore, genomics research studies on mastitis have been conducted and SNPs on Bos Taurus autosome 4 (BTA4) and BTA18 were found to be significantly associated with mastitis [87]. Furthermore, 665 interactions in more than 140 genes were found in a co-expression network via the Genemania gene network analysis, which were recognized as candidate QTL for mastitis in the Holstein cows [88].

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5. Transcriptomics in milk protein research

The transcriptome broadly refers to the sum of all RNAs transcribed by organism, tissues, or cells in a specific state or period. And its field can be classified by different RNA types or methodology [89]. Since gene expression is complex and involves a variety of regulatory mechanisms, such as histone modification, promoter region, variable shearing, all of which affect the intracellular genes expression and play a regulatory role [90]. The expression level of genes among different tissues or cells is not consistent; hence, the complex and variable functions can be performed during different condition of physiological and pathological [91].

Methods of transcriptomics are similar to genomics, including microarray and RNA sequencing, while the latter one overcomes the weakness of Sanger sequencing due to the higher accuracy as well as sensitivity. Nowadays, the next-generation platforms such as Illumia, SOLID, and 454 are commonly used in related research studies to obtain reads and the transcript assembled, which revolutionize the analysis of eukaryotic transcriptomic [92]. In research studies related to lactating dairy cows, the expression profiles of mRNA were more focused especially in mammary glands, to reveal the candidate genes related to lactation. While the long noncoding RNAs also contribute to the pathway regulations in mammary gland and are essential for breeding [93]. However, the quality as well as quantity of RNA determines the reliability of sequencing results, so the extraction of total RNA from mammary gland significantly affects the analysis of the transcriptome. Li et al. reviewed the RNA sources used in transcriptome of lactating bovine mammary gland [9], which were used to the investigate the mammary gland development, effects of nutritional management on synthesis of milk composition, etc.

To specifically investigate the synthesis of milk protein, former studies revealed that the insulin signaling and mammalian target of rapamycin (mTOR) pathway participate in the regulation of milk protein synthesis by RNA-seq [94]. MenziesK et al. demonstrated that insulin plays a pivotal role in regulating milk proteins in dairy cows, while the recent works also report the similar results in other mammal animals [95]. Insulin was found to both directly and indirectly regulate the milk protein synthesis that is the involvement of control in gene expression and the regulation in translation [96]. Specifically, insulin can strongly activate the STAT5 pathway by increasing phosphorylation of the transcription factor. While the expression of ELF5 is induced by insulin in mammary tissue of dairy cows, which can co-activate and amplify the STAT5 [97]. In addition, insulin can regulate amount of translation via the mTOR hence indirectly control milk protein synthesis. mTOR particularly MTORC1 among the two mTOR complexes was well defined to play an important role in regulate protein synthesis by affecting the translation in all tissues of mammals [94]. Protein synthesis in mammal is inhibited by the association of the unphosphorylated eukaryotic translation initiation factor 4E binding protein 1 (4EBP1) with the eukaryotic translation initiation factor 4E (eIF4E), the insulin can increase the specific phosphorylation in mTOR, which in turn phosphorylates 4EBP1 and results in releasing of eiF4E. eiF4E participates in the formation of the translation initiation complex and hence initiates the translation of mRNA into protein [98]. Furthermore, there are also additional mechanisms of activated mTOR complex to enhance the translation process through phosphorylation of the ribosomal protein S6 kinase (S6K1) and ukaryotic elongation factor-2 kinase (EEF2K) [99].

Except for the synthesis mechanism, transcriptomics conducted in investigation of nutritional management. The different expression of genes in milk synthesis was found in factors including short-term feeding restriction, low-quality total mixed ration, inducing the reduction in milk protein associated with the downregulation of protein synthesis [100, 101]. While the management such as the frequency of milking also causes the perturbation in lactation, former study reported that the increased milking frequency affects the expression of genes involved in reconstruction of extracellular matrix, κ-CN, α-lactalbumin, which may affect the milk protein components [102, 103]. Moreover, the related research studies also reported the perturbation of expression on milk protein synthesis induced by condition changes. For example, Gao et al. found that dairy cows suffered heat stress upregulated the inflammation-related genes, which interfered and downregulated the milk protein synthesis [104].

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6. Proteomics in milk protein research

Proteomics is defined as the technology of protein expressions from transcription and translation. By analyzing the posttranslational modification meanwhile identifying the differential proteins [105], the interaction among proteins, proteomics reflects the body metabolic changes to internal and external environmental changes and reveals biological functions inside. The advancement of analytical techniques pushes the development of proteomics rapidly. Two-dimensional electrophoresis (2-DE) is a well-developed technology and was used to separate proteins in the past decade [106]. As early as 1977, O’Farrel used 2-DE technology to separate about 1100 proteins from E. coli[107], which proved that 2-DE technology has the characteristics of high resolution and high sensitivity and is effective for analyzing complex biological samples and separating proteins.

The 2-DE technology performs one-dimensional isoelectric focusing according to different isoelectric points of proteins and then separates proteins of different molecular weights by polyacrylamide gel electrophoresis [108]. The 2-DE formed by the combination of these two technologies effectively separates protein vesicles in both directions of charge and relative molecular mass. Therefore, the information of the differential protein can be obtained through subsequent mass spectrometry identification and combined with bioinformatics analysis to analyze its biological function. The application of 2-DE combined with MS was usually used to identify the biomarkers related to treatment [109]. However, quantitative proteomics is challenging the 2-DE and MS methods as it allows for the massive multiplexing of primary data with better quality than established methods [110]. The method of quantitative proteomics, the isobaric tags for absolute and relative quantification (iTRAQ) combined with MS, is commonly employed to analyze the multiplicity of different samples; however, the accuracy of iTRAQ might be compromised due to the influence of near isobaric ions contamination in a sample [111]. In fact, the methods of 2-DE combined with MS and iTRAQ have been widely selected in research related to lactating cows, particularly in the investigations of mastitis and effects of nutritional management.

As a novel research approach, proteomics was conducted to investigate the milk protein including the milk protein profile and the MFGM components. The investigation of lactation periods found the alternation of whey proteome as evidenced by the significantly decreased content of immunoglobulins and caseins and in particular the colostrum at 48 h postpartum [112]. While in mid-lactation, Reinhardt et al. found that the proteins associated with lipid transportation, synthesis, and secretion are upregulated, and 120 proteins were identified to associate with cell signaling and membrane/protein trafficking [113]. Except for the milk from different periods, the proteomic studies also focus on the milk components different among different species. For example, β-LG lacks in camel milk, while it is the main whey protein in the caprine and bovine [114]. This technology can also be used to identify the adulterated milk products meanwhile getting the information of the sources of hypoallergenic replacements. By the application of iTRAQ and MS, specific proteins from different species can be classified and be used for characterizing. For example, primary amine oxidase is unique in cows, while biglycan is source of goat [115, 116]. Furthermore, the investigation of MFGM profiles meanwhile provides the overview of MFGM proteome among species [117], which indicated that these differences of protein components may be related to differences in heredity.

The application of proteomics in pathology such as mastitis has been conducted to find biomarkers to overcome the challenges of quantification in mastitis diagnosing. While proteins including hemoglobin β, cytochrome C oxidase, annexin V, and α-1-acid glycoprotein as well as collagen type I α 1 and inter-α (Globulin) inhibitor H4 show more abundance in dairy cows that suffered mastitis [118, 119], which may participate in the repairment of tissue damage.

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7. Metabolomics in milk protein research

Metabolomics focus on the quantitatively analyzing of all metabolites in body to find the relative relationship between metabolites and physiological changes. Most of its research objects are small molecular substances with a relative molecular mass of less than 1000. In recent years, studies have reported the effects of different environmental factors on small molecular metabolites in animals and plants. While metabolic map was drawn through in-depth research on the metabolites of the body to seek the biomarkers [120, 121]. Moreover, analysis of NMR and MS indicated that biomarkers such as phosphorylated saccharides, acetone, and β-hydroxybutyrate (high levels) are closely correlated with the metabolic status in dairy cows during early lactation [9], which may contribute to the breeding selection to alleviate the metabolic stress in dairy cows during early lactation.

Similar to the application of proteomics in searching unique biomarkers, the investigation using NMR metabolomics approach found that acetate and novel metabolites including hippurate, isoleucine, butyrate, fumarate, and β-hydroxybutyrate are associated with milk composition [122]. While improving abundance of volatile fatty acid (VFA) as well as β-hydroxybutyrate and low abundance of hippurate and fumarate in milk are coupled with high levels of somatic cells [123], which contribute to the potential biomarkers for milk quality when dairy cows in high SCC conditions. Furthermore, metabolomics also provides new approach on highlighting interspecies differences from analyzing the metabolites. By using NMR and LC–MS or GC–MS method, the unique metabolites in milk among horse, Jersey cow, camel, yak, goat, caprine, buffalo, and dairy cow were found respectively, and results validated that metabolomics is a feasible approach for milk composition analysis [124, 125].

Although metabolomics has a higher accuracy and the high-throughput abilities, its application is still in the junior stages in research studies related to lactation especially the milk protein. With the advantage of combination with multivariate data analysis tool, metabolomics will obviously push the process of lactation research in the future. While the unique metabolites identified by these technologies will also provide much better perspective for the investigation of milk protein.

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8. Conclusions

The synthesis of milk protein is complex in mammary gland and is regulated by multiple factors, the protein components in milk are specific with the mammary tissue since they are minor or no expressions in the rest organs. Several hormones including insulin participate in the regulation of milk protein synthesis with a pivotal role of perturbation pathway such as mTOR. However, the control of milk synthesis is still need to be completely understood, to open new insight of research not previously considered. The advent of Omics technologies provides the possibilities to further investigate related complex mechanisms. These novel research approaches combined with bioinformatics constitute to be useful and powerful to generate large datasets for lactation sciences, which contribute to reveal the mechanism of milk protein synthesis and the novel biomarkers in milk affected by some factors. However, considering the limitation of cost, reproducibility, and throughput, it should be well arranged and prepared when choosing these new research approaches.

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Funding

The present study was financially supported by the National Natural Science Foundation of China (31872383), the Agriculture Science and Technology Innovation Program (ASTIP-IAS07-1) and the Key Research and Development Program of the Ningxia Hui Autonomous Region (2021BEF02018).

References

  1. 1. Ha E, Zemel MB. Functional properties of whey, whey components, and essential amino acids: Mechanisms underlying health benefits for active people (review). Journal of Nutritional Biochemistry. 2003;14(5):251-258
  2. 2. Guo Z, Gao S, Ouyang J, Ma L, Bu D. Impacts of heat stress-induced oxidative stress on the Milk protein biosynthesis of dairy cows. Animals. 2021;11(3):726
  3. 3. Rhoads ML, Rhoads RP, VanBaale MJ, Collier RJ, Sanders SR, Weber WJ, et al. Effects of heat stress and plane of nutrition on lactating Holstein cows: I. production, metabolism, and aspects of circulating somatotropin. Journal of Dairy Science. 2009;92(5):1986-1997
  4. 4. Bionaz M, Loor JJ. Gene networks driving bovine milk fat synthesis during the lactation cycle. BMC Genomics. 2008;9(1):366
  5. 5. Ayadi M, Caja G, Such X, Knight CH. Effect of omitting one milking weekly on lactational performances and morphological udder changes in dairy cows. Journal of Dairy Science. 2003;86(7):2352-2358
  6. 6. Gao ST, Guo J, Quan SY, Nan XM, Fernandez MVS, Baumgard LH, et al. The effects of heat stress on protein metabolism in lactating Holstein cows. Journal of Dairy Science. 2017;100(6):5040-5049
  7. 7. Nooren IM, Thornton JM. Diversity of protein-protein interactions. The EMBO Journal. 2003;22(14):3486-3492
  8. 8. Vailati-Riboni M, Palombo V, Loor JJ. What are omics sciences? In: Periparturient Diseases of Dairy Cows. Switzerland: Springer; 2017. pp. 1-7
  9. 9. Li S, Wang Q , Lin X, Jin X, Liu L, Wang C, et al. The use of “omics” in lactation research in dairy cows. International Journal of Molecular Sciences. 2017;18(5):983
  10. 10. Szwajkowska M, Wolanciuk A, Barłowska J, Krol J, Litwińczuk Z. Bovine milk proteins as the source of bioactive peptides influencing the consumers’ immune system–a review. Animal Science Papers and Reports. 2011;29(4):269-280
  11. 11. NG-Kwai-Hang KF, Hayes JF, Moxley JE, Monardes HG. Variation in milk protein concentrations associated with genetic polymorphism and environmental factors. Journal of Dairy Science. 1987;70(3):563-570
  12. 12. Livney YD. Milk proteins as vehicles for bioactives. Current Opinion in Colloid & Interface Science. 2010;15(1-2):73-83
  13. 13. De Wit JN. Marschall Rhone-Poulenc award lecture. Nutritional and functional characteristics of whey proteins in food products. Journal of Dairy Science. 1998;81(3):597-608
  14. 14. Azarpazhooh A, Limeback H. Clinical efficacy of casein derivatives: A systematic review of the literature. Journal of the American Dental Association. 2008;139(7):915-924. quiz 994-5
  15. 15. Hipp N, Groves ML, Custer J, McMeekin T. Separation of α-, β-and γ-casein. Journal of Dairy Science. 1952;35(3):272-281
  16. 16. Kilara A, Vaghela M. Whey proteins. In: Proteins in Food Processing. Sawston, UK: Elsevier; 2018. pp. 93-126
  17. 17. Demmelmair H, Prell C, Timby N, Lonnerdal B. Benefits of Lactoferrin, Osteopontin and Milk fat globule membranes for infants. Nutrients. 2017;9(8):817
  18. 18. Cross KJ, Huq NL, Palamara JE, Perich JW, Reynolds EC. Physicochemical characterization of casein phosphopeptide-amorphous calcium phosphate nanocomplexes. Journal of Biological Chemistry. 2005;280(15):15362-15369
  19. 19. Molino ACT, Aline C. Effects of Enzymatic Dephosphorylation on Properties of Bovine Casein. Canada, Ottawa: McGill University; 2006 [dissertation]
  20. 20. McMahon DJ, Brown RJ. Composition, structure, and integrity of casein micelles: A review. Journal of Dairy Science. 1984;67(3):499-512
  21. 21. McMahon DJ, Oommen BS. Supramolecular structure of the casein micelle. Journal of Dairy Science. 2008;91(5):1709-1721
  22. 22. Plank J, Bian H. Method to assess the quality of casein used as superplasticizer in self-levelling compounds. Cement and Concrete Research. 2010;40(5):710-715
  23. 23. Horne DS. A balanced view of casein interactions. Current Opinion in Colloid & Interface Science. 2017;28:74-86
  24. 24. Bigelow CC. On the average hydrophobicity of proteins and the relation between it and protein structure. Journal of Theoretical Biology. 1967;16(2):187-211
  25. 25. Heinecke JW, Rosen H, Suzuki LA, Chait A. The role of sulfur-containing amino acids in superoxide production and modification of low density lipoprotein by arterial smooth muscle cells. Journal of Biological Chemistry. 1987;262(21):10098-10103
  26. 26. Orsini S, Parlanti F, Bonaduce I. Analytical pyrolysis of proteins in samples from artistic and archaeological objects. Journal of Analytical and Applied Pyrolysis. 2017;124:643-657
  27. 27. Liang L, Luo Y. Casein and pectin: Structures, interactions, and applications. Trends in Food Science and Technology. 2020;97:391-403
  28. 28. Horne DS. Casein interactions: Casting light on the black boxes, the structure in dairy products. International Dairy Journal. 1998;8(3):171-177
  29. 29. Swaisgood HE. Chemistry of milk protein. Developments in Dairy Chemistry. 1982;1:1-59
  30. 30. Noelken M, Reibstein M. Conformation of beta-casein B. Archives of Biochemistry and Biophysics. 1968;123(2):397-402
  31. 31. Wang W, Nema S, Teagarden D. Protein aggregation--pathways and influencing factors. International Journal of Pharmaceutics. 2010;390(2):89-99
  32. 32. Tai M, Kegeles G. A micelle model for the sedimentation behavior of bovine beta-casein. Biophysical Chemistry. 1984;20(1-2):81-87
  33. 33. Creamer LK, Plowman JE, Liddell MJ, Smith MH, Hill JP. Micelle stability: Kappa-casein structure and function. Journal of Dairy Science. 1998;81(11):3004-3012
  34. 34. Groves, M. L.; Wickham, E. D.; Farrell, H. M., Jr., Environmental effects on disulfide bonding patterns of bovine kappa-casein. Journal of Protein Chemistry 1998, 17 (2), 73-84.
  35. 35. Phadungath C. Casein micelle structure: a concise review. Songklanakarin Journal of Science and Technology. 2005;27(1):201-212
  36. 36. Yukalo V, Storozh L. Isolation of κ-CN-1P and β-CN-5P fractions from native casein micelles. The Ukrainian. Biochemical Journal. 2018;90(4):74-79
  37. 37. Altmann K, Wutkowski A, Klempt M, Clawin-Rädecker I, Meisel H, Lorenzen PC. Generation and identification of anti-inflammatory peptides from bovine β-casein using enzyme preparations from cod and hog. Journal of the Science of Food and Agriculture. 2016;96(3):868-877
  38. 38. Myronovskij S, Negrych N, Nehrych T, Starykovych M, Tkachenko V, Yukalo V, et al. Isolation and characterization of peptides from blood serum of patients with multiple sclerosis. Studia. Biologicals. 2015;9(2):51-58
  39. 39. Smithers GW. Whey and whey proteins—From ‘gutter-to-gold’. International Dairy Journal. 2008;18(7):695-704
  40. 40. Luhovyy BL, Akhavan T, Anderson GH. Whey proteins in the regulation of food intake and satiety. Journal of the American College of Nutrition. 2007;26(6):704S-712S
  41. 41. Csapó-Kiss Z, Stefler J, Martin T, Makray S, Csapó J. Composition of mares' colostrum and milk. Protein content, amino acid composition and contents of macro and micro-elements. International Dairy Journal. 1995;5(4):403-415
  42. 42. Liu Y, Wang X, Hu CA. Therapeutic potential of amino acids in inflammatory bowel disease. Nutrients. 2017;9(9):920
  43. 43. Fox PF, Mulvihill DM. Milk proteins: Molecular, colloidal and functional properties. Journal of Dairy Research. 1982;49(4):679-693
  44. 44. Pérez MD, Calvo M. Interaction of β-lactoglobulin with retinol and fatty acids and its role as a possible biological function for this protein: A review. Journal of Dairy Science. 1995;78(5):978-988
  45. 45. Sawyer L. β-Lactoglobulin. In: Advanced Dairy Chemistry. New York: Springer; 2013. pp. 211-259
  46. 46. Morrison J, Ebner K. Studies on galactosyltransferase: Kinetic effects of α-lactalbumin with N-acetylglucosamine and glucose as galactosyl group acceptors. Journal of Biological Chemistry. 1971;246(12):3992-3998
  47. 47. Kilara A. Whey and whey products. Dairy Processing Quality Assurance. 2008;1:337-355
  48. 48. Nielsen LR, Nielsen SB, Zhao Z, Olsen K, Nielsen JH, Lund MN. Control of alpha-Lactalbumin aggregation by modulation of temperature and concentration of calcium and cysteine. Journal of Agricultural and Food Chemistry. 2018;66(27):7110-7120
  49. 49. Shamay A, Homans R, Fuerman Y, Levin I, Barash H, Silanikove N, et al. Expression of albumin in nonhepatic tissues and its synthesis by the bovine mammary gland. Journal of Dairy Science. 2005;88(2):569-576
  50. 50. Spector AA, John K, Fletcher JE. Binding of long-chain fatty acids to bovine serum albumin. Journal of Lipid Research. 1969;10(1):56-67
  51. 51. Butler JE. Bovine immunoglobulins: A review. Journal of Dairy Science. 1969;52(12):1895-1909
  52. 52. Manion B. Compositional and Functional Properties of Fractions Rich in Milk Fat Globule Membrane Material. Ontario, Canada: University of Guelph; 2007
  53. 53. Danthine S, Blecker C, Paquot M, Innocente N, Deroanne C. Progress in milk fat globule membrane research: A review. Le Lait. 2000;80(2):209-222
  54. 54. Cavaletto M, Giuffrida MG, Conti A. Milk fat globule membrane components--a proteomic approach. Advances in Experimental Medicine and Biology. 2008;606:129-141
  55. 55. Zavaleta N, Kvistgaard AS, Graverholt G, Respicio G, Guija H, Valencia N, et al. Efficacy of an MFGM-enriched complementary food in diarrhea, anemia, and micronutrient status in infants. Journal of Pediatric Gastroenterology and Nutrition. 2011;53(5):561-568
  56. 56. Dewettinck K, Rombaut R, Thienpont N, Le TT, Messens K, Van Camp J. Nutritional and technological aspects of milk fat globule membrane material. International Dairy Journal. 2008;18(5):436-457
  57. 57. Keenan TW. Historical perspective: Milk lipid globules and their surrounding membrane: A brief history and perspectives for future research. Journal of Mammary Gland Biology and Neoplasia. 2001;6(3):365-371
  58. 58. Evers JM. The milkfat globule membrane—Compositional and structural changes post secretion by the mammary secretory cell. International Dairy Journal. 2004;14(8):661-674
  59. 59. Mather IH. A review and proposed nomenclature for major proteins of the milk-fat globule membrane. Journal of Dairy Science. 2000;83(2):203-247
  60. 60. Nishino T, Okamoto K, Eger BT, Pai EF. 5 the xanthine oxidoreductase enzyme family: Xanthine dehydrogenase, xanthine oxidase, and aldehyde oxidase. In: Volume 2 Complex Flavoproteins, Dehydrogenases and Physical Methods, De Gruyter. Berlin, Boston: Walter de Gruyter GmbH; 2013. pp. 103-124. Available from:https://books.google.com.hk/books?hl=en&lr=&id=5a_pBQAAQBAJ&oi=fnd&pg=PR5&dq=Handbook+of+Flavoproteins:+Complex+Flavoproteins,+Dehydrogenases+and+Physical+Methods&ots=vYfyogkivI&sig=_xNVrJkkj-1fEq87STwOJsUBUG0&redir_esc=y#v=onepage&q=Handbook%20of%20Flavoproteins%3A%20Complex%20Flavoproteins%2C%20Dehydrogenases%20and%20Physical%20Methods&f=false
  61. 61. Martin HM, Hancock JT, Salisbury V, Harrison R. Role of xanthine oxidoreductase as an antimicrobial agent. Infection and Immunity. 2004;72(9):4933-4939
  62. 62. Abeler-Dorner L, Swamy M, Williams G, Hayday AC, Bas A. Butyrophilins: An emerging family of immune regulators. Trends in Immunology. 2012;33(1):34-41
  63. 63. Karunakaran MM, Herrmann T. The Vγ9Vδ2 T cell antigen receptor and butyrophilin 3 A1 (BTN3A1): Models of interaction, the possibility of co-evolution, and the case of dendritic epidermal T cells. Frontiers in Immunology. 2014;5:648
  64. 64. Borba VV, Lerner A, Matthias T, Shoenfeld Y. Bovine milk proteins as a trigger for autoimmune diseases: Myth or reality? International Journal. 2020;8(1):10-21
  65. 65. Sun Y, Wang C, Sun X, Guo M. Comparative proteomics of whey and Milk fat globule membrane proteins of Guanzhong goat and Holstein cow mature Milk. Journal of Dairy Science. 2019;84(2):244-253
  66. 66. Aziz M, Jacob A, Matsuda A, Wang P. Review: Milk fat globule-EGF factor 8 expression, function and plausible signal transduction in resolving inflammation. Apoptosis. 2011;16(11):1077-1086
  67. 67. Nakatani H, Aoki N, Nakagawa Y, Jin-No S, Aoyama K, Oshima K, et al. Weaning-induced expression of a milk-fat globule protein, MFG-E8, in mouse mammary glands, as demonstrated by the analyses of its mRNA, protein and phosphatidylserine-binding activity. Biochemical Journal. 2006;395(1):21-30
  68. 68. Peterson JA, Scallan CD, Ceriani RL, Hamosh M. Structural and functional aspects of three major glycoproteins of the human milk fat globule membrane. Advances in Experimental Medicine and Biology. 2001;501:179-187
  69. 69. Cranford SW, De Boer J, Van Blitterswijk C, Buehler MJ. Materiomics: An-omics approach to biomaterials research. Advanced Materials. 2013;25(6):802-824
  70. 70. Rochfort S. Metabolomics reviewed: A new "omics" platform technology for systems biology and implications for natural products research. Journal of Natural Products. 2005;68(12):1813-1820
  71. 71. Bustamante CD, Burchard EG, De la Vega FM. Genomics for the world. Nature. 2011;475(7355):163-165
  72. 72. Hegde PS, White IR, Debouck C. Interplay of transcriptomics and proteomics. Current Opinion in Biotechnology. 2003;14(6):647-651
  73. 73. Dettmer K, Aronov PA, Hammock BD. Mass spectrometry-based metabolomics. Mass Spectrometry Reviews. 2007;26(1):51-78
  74. 74. Varshney RK, Graner A, Sorrells ME. Genomics-assisted breeding for crop improvement. Trends in Plant Science. 2005;10(12):621-630
  75. 75. Amigo L, Recio I, Ramos M. Genetic polymorphism of ovine milk proteins: Its influence on technological properties of milk—A review. International Dairy Journal. 2000;10(3):135-149
  76. 76. Barillet F. Genetic improvement for dairy production in sheep and goats. Small Ruminant Research. 2007;70(1):60-75
  77. 77. Bilal G, Cue R, Hayes J. Genetic and phenotypic associations of type traits and body condition score with dry matter intake, milk yield, and number of breedings in first lactation Canadian Holstein cows. Canadian Journal of Animal Science. 2016;96(3):434-447
  78. 78. Cohen-Zinder M, Donthu R, Larkin DM, Kumar CG, Rodriguez-Zas SL, Andropolis KE, et al. Multisite haplotype on cattle chromosome 3 is associated with quantitative trait locus effects on lactation traits. Physiological Genomics. 2011;43(21):1185-1197
  79. 79. Berkowicz EW, Magee DA, Sikora KM, Berry DP, Howard DJ, Mullen MP, et al. Single nucleotide polymorphisms at the imprinted bovine insulin-like growth factor 2 (IGF2) locus are associated with dairy performance in Irish Holstein-Friesian cattle. Journal of Dairy Research. 2011;78(1):1-8
  80. 80. Veerkamp R, Mulder H, Thompson R, Calus M. Genomic and pedigree-based genetic parameters for scarcely recorded traits when some animals are genotyped. Journal of Dairy Science. 2011;94(8):4189-4197
  81. 81. Bobe G, Beitz DC, Freeman AE, Lindberg GL. Effect of milk protein genotypes on milk protein composition and its genetic parameter estimates. Journal of Dairy Science. 1999;82(12):2797-2804
  82. 82. Boettcher PJ, Caroli A, Stella A, Chessa S, Budelli E, Canavesi F, et al. Effects of casein haplotypes on milk production traits in Italian Holstein and Brown Swiss cattle. Journal of Dairy Science. 2004;87(12):4311-4317
  83. 83. Li L. Physical Mapping of Two Multi-Gene Families and Comparative Anchor Loci in Cattle and Genetic Linkage Analysis on Cattle Chromosome 6. Texas A&M University; 1993 [phD thesis]
  84. 84. Heck J, Olieman C, Schennink A, Van Valenberg H, Visker M, Meuldijk R, et al. Estimation of variation in concentration, phosphorylation and genetic polymorphism of milk proteins using capillary zone electrophoresis. International Dairy Journal. 2008;18(5):548-555
  85. 85. Klopfenstein JJ. Dairy herd health for optimal reproduction. Bovine Reproduction. 2021:517-525
  86. 86. Moyes KM, Drackley JK, Morin DE, Bionaz M, Rodriguez-Zas SL, Everts RE, et al. Gene network and pathway analysis of bovine mammary tissue challenged with streptococcus uberis reveals induction of cell proliferation and inhibition of PPARγ signaling as potential mechanism for the negative relationships between immune response and lipid metabolism. BMC Genomics. 2009;10(1):1-29
  87. 87. Wijga S, Bastiaansen JW, Wall E, Strandberg E, de Haas Y, Giblin L, et al. Genomic associations with somatic cell score in first-lactation Holstein cows. Journal of Dairy Science. 2012;95(2):899-908
  88. 88. Tiezzi F, Parker-Gaddis KL, Cole JB, Clay JS, Maltecca C. A genome-wide association study for clinical mastitis in first parity US Holstein cows using single-step approach and genomic matrix re-weighting procedure. PLoS One. 2015;10(2):e0114919
  89. 89. Lowe R, Shirley N, Bleackley M, Dolan S, Shafee T. Transcriptomics technologies. PLoS Computational Biology. 2017;13(5):e1005457
  90. 90. Karlic R, Chung HR, Lasserre J, Vlahovicek K, Vingron M. Histone modification levels are predictive for gene expression. Proceedings of the National Academy of Sciences of the United States of America. 2010;107(7):2926-2931
  91. 91. Perou CM, Jeffrey SS, van de Rijn M, Rees CA, Eisen MB, Ross DT, et al. Distinctive gene expression patterns in human mammary epithelial cells and breast cancers. Proceedings of the National Academy of Sciences of the United States of America. 1999;96(16):9212-9217
  92. 92. Mutz K-O, Heilkenbrinker A, Lönne M, Walter J-G, Stahl F. Transcriptome analysis using next-generation sequencing. Current Opinion in Biotechnology. 2013;24(1):22-30
  93. 93. Yang B, Jiao B, Ge W, Zhang X, Wang S, Zhao H, et al. Transcriptome sequencing to detect the potential role of long non-coding RNAs in bovine mammary gland during the dry and lactation period. BMC Genomics. 2018;19(1):605
  94. 94. Wang X, Proud CG. The mTOR pathway in the control of protein synthesis. Physiology (Bethesda). 2006;21(5):362-369
  95. 95. Menzies KK, Lefèvre C, Macmillan KL, Nicholas KR. Insulin regulates milk protein synthesis at multiple levels in the bovine mammary gland. Functional & Integrative Genomics. 2009;9(2):197-217
  96. 96. Cao Y, Liu S, Liu K, Abbasi IHR, Cai C, Yao J. Molecular mechanisms relating to amino acid regulation of protein synthesis. Nutrition Research Reviews. 2019;32(2):183-191
  97. 97. Sandhu GK, Milevskiy MJG, Wilson W, Shewan AM, Brown MA. Non-coding RNAs in mammary gland development and disease. Advances in Experimental Medicine and Biology. 2016;886:121-153
  98. 98. Kimball SR, Jefferson LS. New functions for amino acids: Effects on gene transcription and translation. The American Journal of Clinical Nutrition. 2006;83(2):500S-507S
  99. 99. Schieke, S. M.; Phillips, D.; McCoy, J. P., Jr.; Aponte, A. M.; Shen, R. F.; Balaban, R. S.; Finkel, T., The mammalian target of rapamycin (mTOR) pathway regulates mitochondrial oxygen consumption and oxidative capacity. Journal of Biological Chemistry 2006, 281 (37), 27643-27652.
  100. 100. Ollier S, Robert-Granie C, Bernard L, Chilliard Y, Leroux C. Mammary transcriptome analysis of food-deprived lactating goats highlights genes involved in milk secretion and programmed cell death. Journal of Nutrition. 2007;137(3):560-567
  101. 101. Sigl T, Meyer HH, Wiedemann S. Gene expression analysis of protein synthesis pathways in bovine mammary epithelial cells purified from milk during lactation and short-term restricted feeding. Journal of Animal Physiology and Animal Nutrition. 2014;98(1):84-95
  102. 102. Erdman RA, Varner M. Fixed yield responses to increased milking frequency. Journal of Dairy Science. 1995;78(5):1199-1203
  103. 103. Boutinaud M, Ben Chedly MH, Delamaire E, Guinard-Flament J. Milking and feed restriction regulate transcripts of mammary epithelial cells purified from milk. Journal of Dairy Science. 2008;91(3):988-998
  104. 104. Gao S, Ma L, Zhou Z, Zhou Z, Baumgard LH, Jiang D, et al. Heat stress negatively affects the transcriptome related to overall metabolism and milk protein synthesis in mammary tissue of midlactating dairy cows. Physiological Genomics. 2019;51(8):400-409
  105. 105. Pappireddi N, Martin L, Wuhr M. A review on quantitative multiplexed proteomics. Chembiochem. 2019;20(10):1210-1224
  106. 106. Ye X, Tang J, Mao Y, Lu X, Yang Y, Chen W, et al. Integrated proteomics sample preparation and fractionation: Method development and applications. TrAC Trends in Analytical Chemistry. 2019;120:115667
  107. 107. O'Farrell PZ, Goodman HM, O'Farrell PH. High resolution two-dimensional electrophoresis of basic as well as acidic proteins. Cell. 1977;12(4):1133-1142
  108. 108. Issaq H, Veenstra T. Two-dimensional polyacrylamide gel electrophoresis (2D-PAGE): Advances and perspectives. BioTechniques. 2008;44(5):697-698, 700
  109. 109. Chen J, Zhou C, Liu Z, Fu Y, Zheng P, Yang D, et al. Divergent urinary metabolic phenotypes between major depressive disorder and bipolar disorder identified by a combined GC–MS and NMR spectroscopic metabonomic approach. Journal of Proteome Research. 2015;14(8):3382-3389
  110. 110. Bantscheff M, Lemeer S, Savitski MM, Kuster B. Quantitative mass spectrometry in proteomics: Critical review update from 2007 to the present. Analytical and Bioanalytical Chemistry. 2012;404(4):939-965
  111. 111. Bantscheff M, Schirle M, Sweetman G, Rick J, Kuster B. Quantitative mass spectrometry in proteomics: A critical review. Analytical and Bioanalytical Chemistry. 2007;389(4):1017-1031
  112. 112. Senda A, Fukuda K, Ishii T, Urashima T. Changes in the bovine whey proteome during the early lactation period. Animal Science Journal. 2011;82(5):698-706
  113. 113. Reinhardt TA, Lippolis JD. Developmental changes in the milk fat globule membrane proteome during the transition from colostrum to milk. Journal of Dairy Science. 2008;91(6):2307-2318
  114. 114. Hinz K, O'Connor PM, Huppertz T, Ross RP, Kelly AL. Comparison of the principal proteins in bovine, caprine, buffalo, equine and camel milk. Journal of Dairy Research. 2012;79(2):185-191
  115. 115. Yang Y, Bu D, Zhao X, Sun P, Wang J, Zhou L. Proteomic analysis of cow, yak, buffalo, goat and camel milk whey proteins: Quantitative differential expression patterns. Journal of Proteome Research. 2013;12(4):1660-1667
  116. 116. Hettinga K, van Valenberg H, de Vries S, Boeren S, van Hooijdonk T, van Arendonk J, et al. The host defense proteome of human and bovine milk. PLoS One. 2011;6(4):e19433
  117. 117. Yang Y, Zheng N, Zhao X, Zhang Y, Han R, Ma L, et al. Proteomic characterization and comparison of mammalian milk fat globule proteomes by iTRAQ analysis. Journal of Proteomics. 2015;116:34-43
  118. 118. Eckersall PD, McLaughlin M, Eckersall P, Whitfield P. 10 proteomics in animal health and disease. Methods in Animal Proteomics. 2011;243:5-11
  119. 119. Mansor R. Proteomic and Metabolomic Studies on Milk during Bovine Mastitis. Scotland, UK: University of Glasgow; 2012
  120. 120. Garcia-Sevillano MA, Contreras-Acuna M, Garcia-Barrera T, Navarro F, Gomez-Ariza JL. Metabolomic study in plasma, liver and kidney of mice exposed to inorganic arsenic based on mass spectrometry. Analytical and Bioanalytical Chemistry. 2014;406(5):1455-1469
  121. 121. Wei L, Wang Q , Wu H, Ji C, Zhao J. Proteomic and metabolomic responses of Pacific oyster Crassostrea gigas to elevated pCO2 exposure. Journal of Proteomics. 2015;112:83-94
  122. 122. Sundekilde U, Poulsen NA, Larsen LB, Bertram H. Nuclear magnetic resonance metabonomics reveals strong association between milk metabolites and somatic cell count in bovine milk. Journal of Dairy Science. 2013;96(1):290-299
  123. 123. Boudonck KJ, Mitchell MW, Wulff J, Ryals JA. Characterization of the biochemical variability of bovine milk using metabolomics. Metabolomics. 2009;5(4):375-386
  124. 124. Scano P, Murgia A, Pirisi FM, Caboni P. A gas chromatography-mass spectrometry-based metabolomic approach for the characterization of goat milk compared with cow milk. Journal of Dairy Science. 2014;97(10):6057-6066
  125. 125. Yang Y, Zheng N, Zhao X, Zhang Y, Han R, Yang J, et al. Metabolomic biomarkers identify differences in milk produced by Holstein cows and other minor dairy animals. Journal of Proteomics. 2016;136:174-182

Written By

Zitai Guo, Lu Ma and Dengpan Bu

Submitted: December 24th, 2021 Reviewed: January 5th, 2022 Published: April 7th, 2022