Changes in Milk Proteome and Metabolome Associated with Dry Period Length, Energy Balance, and Lactation Stage in Postparturient Dairy Cows

Comprehensive review of milk fat globule membrane proteins across mammals and lactation periods in health and disease

Milk fat globule membrane (MFGM) is a three-layer membrane-like structure encasing natural milk fat globules (MFGs). MFGM holds promise as a nutritional supplement because of the numerous physiological functions of its constituent protein. This review summarizes and compares the differences in MFGM protein composition across various species, including bovines, goats, camels, mares, and donkeys, and different lactation periods, such as colostrum and mature milk, as assessed by techniques such as proteomics and mass spectrometry. We also discuss the health benefits of MFGM proteins throughout life. MFGM proteins promote intestinal development, neurodevelopment, and glucose and lipid metabolism by upregulating tight junction protein expression, brain function-related genes, and glucose and fatty acid biosynthesis processes. We focus on the mechanisms underlying these beneficial effects of MFGM proteins. MFGM proteins activate key substances in in signaling pathways, such as the phosphatidylinositol 3-kinase/protein kinase B, mitogen-activated protein kinase, and myosin light chain kinase signaling pathways. Overall, the consumption of MFGM proteins plays an essential role in conferring health benefits, some of which are important throughout the mammalian life cycle.

Milk fat globule membrane proteins are crucial in regulating lipid digestion during simulated in vitro infant gastrointestinal digestion

Products of lipolysis released during digestion positively affect the metabolism of newborns. In contrast to the 3-layer biological membranes covering human milk (HM) fat, the lipid droplets in infant milk formula (IMF) are covered by a single membrane composed of casein and whey proteins. To reduce the differences in lipid structure between IMF and HM, studies have used milk fat globule membrane (MFGM) components such as milk polar lipids (MPL) to prepare emulsions mimicking HM fat globules However, few studies have elucidated the effect of membrane proteins (MP) on lipid digestion in infants. In this study, 3 kinds of emulsions were prepared: One with MPL as the interfaced of lipid droplets (RE-1), one with membrane protein concentrate (MPC) (RE-2) as the interface of lipid droplets, and one with both MPL and MPC (1:2) as the co-interface of lipid droplets (RE-3). The interfacial coverage of the emulsions was confirmed by measuring the contents of MPL and MPC at the lipid droplet interface, and by confocal laser scanning microscopy analyzed. By controlling the homogenization intensity, the specific surface area of lipid droplets was controlled at the same level among the 3 emulsions. The stability constants of the emulsions varied, and RE-1 was the most stable. During simulated in vitro infant gastrointestinal digestion, the amount of free fatty acids (FFA) released from the lipid droplets was significantly higher from those with MPC at the interface (RE-2, RE-3) than from that with MPL at the interface (RE-1). The amount of FFA released at the end of intestinal digestion of RE-1, RE-2, and RE-3 was 255.00 ± 3.54 µmol,328.75 ± 5.30 µmol, 298.50 ± 9.19 µmol, respectively. Compared with the lipid droplets in RE-2, those with MPL at the interface (RE-1, RE-3) released more unsaturated fatty acids (USFAs) during digestion. The emulsifying activity index was highest in RE-3 (MPL and MPC co-interface). The presence of MPL at the emulsion interface increased the release of USFAs, while the presence of MPC increased the release of FFA. These results show that both MPL and MP are indispensable in the construction of MFGM. Understanding their effects on digestion can provide new strategies for the development of infant foods.

Non-targeted metabolomics identifies biomarkers in milk with high and low milk fat percentage

Milk is widely recognized as an important food source with health benefits. Different consumer groups have different requirements for the content and proportion of milk fat; therefore, it is necessary to investigate the differential metabolites and their regulatory mechanisms in milk with high and low milk fat percentages (MFP). In this study, untargeted metabolomics was performed on milk samples from 13 cows with high milk fat percentage (HF) and 13 cows with low milk fat percentage (LF) using ultra-high performance liquid chromatography coupled with mass spectrometry (UHPLC-MS/MS). Forty-eight potential differentially labeled compounds were screened using the orthogonal partial least squares-discriminant analysis (OPLS-DA) combined with the weighted gene co-expression network analysis (WGCNA) method. Amino acid metabolism was the key metabolic pathway with significant enrichment of L-histidine, 5-oxoproline, L-aspartic acid, and L-glutamic acid. The negative correlation with MFP differentiated the HF and LF groups. To further determine the potential regulatory role of these amino acids on milk fat metabolism, the expression levels of marker genes in the milk fat synthesis pathway were explored. It was noticed that L-histidine reduced milk fat concentration primarily by inhibiting the triglycerides (TAG) synthesis pathway. L-aspartic acid and L-glutamic acid inhibited milk fat synthesis through the fatty acid de novo and TAG synthesis pathways. This study provides new insights into the mechanism underlying milk fat synthesis and milk quality improvement.

Protective mechanism of milk fat globule membrane proteins on Lactobacillus acidophilus CICC 6074 under acid stress based on proteomic analysis

The prerequisite for lactic acid bacteria to perform their probiotic function is that they could survive the acid-stressed environment of production and application. In this experiment, the protective mechanism of milk fat globule membrane (MFGM) proteins on lactic acid bacteria under acid stress was investigated. Scanning electron microscopy and fluorescence probe were used to analyze the condition of the acid-treated bacteria, which showed that MFGM proteins could enhance the survival ability of Lactobacillus acidophilus CICC 6074 under acid stress by maintaining cell morphology, elevating intracellular pH and H+-ATPase activity. Furthermore, Tandem Mass Tags (TMT) proteomic analysis revealed that MFGM protein could exert protective effects on L. acidophilus CICC 6074 by regulating amino acid metabolism, ATPase activity, peptidoglycan synthesis, gene repair and heritage, etc. The results will provide a new approach for the protection and development of functional lactic acid bacteria.

Efficient Quantification of Milk Metabolites from 1H NMR Spectra Using the Signature Mapping (SigMa) Approach: Chemical Shift Library Development for Cows' Milk and Colostrum

Cow milk contains essential nutrients for humans, and its bulk composition is usually analyzed using Fourier transform infrared spectroscopy. The higher sensitivity of nuclear magnetic resonance (NMR) spectroscopy can augment the extractible qualitative and quantitative information from milk to nearly 60 compounds, enabling us to monitor the health of cows and milk quality. Proton (1H) NMR spectroscopy produces complex spectra that require expert knowledge for identifying and quantifying metabolites. Therefore, an efficient and reproducible methodology is required to transform complex milk 1H NMR spectra into annotated and quantified milk metabolome data. In this study, standard operating procedures for screening the milk metabolome using 1H NMR spectra are developed. A chemical shift library of 63 milk metabolites was established and implemented in the open-access Signature Mapping (SigMa) software. SigMa is a spectral analysis tool that transforms 1H NMR spectra into a quantitative metabolite table. The applicability of the proposed methodology to whole milk, skim milk, and ultrafiltered milk is demonstrated, and the method is tested on ultrafiltered colostrum samples from dairy cows (n = 88) to evaluate whether metabolic changes in colostrum may reflect the metabolic status of cows.

Impact of Environmental Exposures on Human Breast Milk Lipidome in Future Immune-Mediated Diseases

The composition of human breast milk (HBM) exhibits significant variability both between individuals and within the same individual. While environmental factors are believed to play a role in this variation, their influence on breast milk composition remains inadequately understood. Herein, we investigate the impact of environmental factors on HBM lipid composition in a general population cohort. The study included mothers (All Babies In Southeast Sweden study) whose children later progressed to one or more immune-mediated diseases later in life: type 1 diabetes (n = 9), celiac disease (n = 24), juvenile idiopathic arthritis (n = 9), inflammatory bowel disease (n = 7), hypothyroidism (n = 6), and matched controls (n = 173). Lipidome of HBM was characterized by liquid chromatography combined with high-resolution mass spectrometry. We observed that maternal age, body mass index, diet, and exposure to perfluorinated alkyl substances (PFASs) had a marked impact on breast milk lipidome, with larger changes observed in the milk of those mothers whose children later developed autoimmune diseases. We also observed differences in breast milk lipid composition in those mothers whose offspring later developed autoimmune diseases. Our study suggests that breast milk lipid composition is modified by a complex interaction between genetic and environmental factors, and, importantly, this impact was significantly more pronounced in those mothers whose offspring later developed autoimmune/inflammatory diseases. Our findings also suggest that merely assessing PFAS concentration may not capture the full extent of the impact of chemical exposures; thus, the more comprehensive exposome approach is essential for accurately assessing the impact of PFAS exposure on HBM and, consequently, on the health outcomes of the offspring.

Effectiveness of mid-infrared spectroscopy for the prediction of cow milk metabolites

Proton nuclear magnetic resonance (¹H NMR) spectroscopy is acknowledged as one of the most powerful analytical methods with cross-cutting applications in dairy foods. To date, the use of ¹H NMR spectroscopy for the collection of milk metabolic profile is hindered by costly and time-consuming sample preparation and analysis. The present study aimed at evaluating the accuracy of mid-infrared spectroscopy (MIRS) as a rapid method for the prediction of cow milk metabolites determined through ¹H NMR spectroscopy. Bulk milk (n = 72) and individual milk samples (n = 482) were analyzed through one-dimensional ¹H NMR spectroscopy and MIRS. Nuclear magnetic resonance spectroscopy identified 35 milk metabolites, which were quantified in terms of relative abundance, and MIRS prediction models were developed on the same 35 milk metabolites, using partial least squares regression analysis. The best MIRS prediction models were developed for galactose-1-phosphate, glycerophosphocholine, orotate, choline, galactose, lecithin, glutamate, and lactose, with coefficient of determination in external validation from 0.58 to 0.85, and ratio of performance to deviation in external validation from 1.50 to 2.64. The remaining 27 metabolites were poorly predicted. This study represents a first attempt to predict milk metabolome. Further research is needed to specifically address whether developed prediction models may find practical application in the dairy sector, with particular regard to the screening of dairy cows' metabolic status, the quality control of dairy foods, and the identification of processed milk or incorrectly stored milk.

Enhanced Goat Milk MUFA Quality via Date Pit Supplementation: A Time-Based Pattern Recognition Analysis Utilizing Agricultural Waste Byproduct

Date pits are agricultural waste byproducts and are available in tons yearly. Milk MUFAs are lipids beneficial for health and sorted out for food product development. This work is aimed at researching the effect of supplementing dairy goats with date pit powder (DPP) as a source of fatty acids (FA), an alternative to enhancing the unsaturated FA in milk and analysed via chemometrics in a 3-month supplementation-based study. Saanen-Boer crossed dairy goats were divided into six groups comprising of control, 10 g and 20 g both for Ajwa DPP (high-quality dates) and Mariami DPP (agricultural waste byproduct), and another 30 g for Mariami DPP only. The supplementation exercise was done daily on each dairy goat. The DPP and milk samples were analysed for its FA profile applying GC-FID and followed by chemometric techniques, namely, PCA and PLS. Results indicated that the n-6/n-3 ratio was the highest for the unsupplemented group compared to the DPP-treated goats with lower n-6/n-3 ratios. The M30 group showcased the most promising health-related class of FAs viewed by 3D PCA and PLS model clustering patterns, in particular monounsaturated FA (MUFA) (C18:1n9c or oleic acid). These results suggest that Mariami DPP supplementation at higher doses and time to lactating Saanen-Boer cross goats can be a means to milk FA quantity and quality enhancement and that chemometrics via pattern recognition can be useful statistical tools when dealing with overwhelming data.

Donkey Colostrum and Milk: How Dietary Probiotics Can Affect Metabolomic Profile, Alkaline Sphingomyelinase and Alkaline Phosphatase Activity

Positive results on animal health, feed efficiency, and milk's nutritional content have been obtained after oral administration of probiotics. The aim of the present study was therefore to evaluate the effect of dietary supplementation with high numbers of multispecies probiotic formulations on the milk metabolomic profiles of alkaline sphingomyelinase (alk-SMase) and alkaline phosphatase (ALP) in donkeys. Twenty animals were randomly allocated to receive either a normal diet (group B) or a supplemented diet (group A). Colostrum and milk samples were obtained within 48 h, at 15 days (supplementation start), and at 45 days after parturition. Different metabolomic profiles were observed between colostrum and milk, as were the concentrations of 12 metabolites that changed following 30 days of probiotic supplementation. Alk-SMase activity was found to be higher in donkey colostrum (vs. milk at 15 days); this enzyme, together with ALP, increased in milk after 30 days of probiotic supplementation. The results of the present study provide new insight into the complex changes in donkey colostrum and milk composition in the first 45 days of lactation and how the milk metabolome can be modulated by probiotic supplementation.

Interrogating the role of the milk microbiome in mastitis in the multi-omics era

There is growing interest in a functional understanding of milk-associated microbiota as there is ample evidence that host-associated microbial communities play an active role in host health and phenotype. Mastitis, characterized by painful inflammation of the mammary gland, is prevalent among lactating humans and agricultural animals and is associated with significant clinical and economic consequences. The etiology of mastitis is complex and polymicrobial and correlative studies have indicated alterations in milk microbial community composition. Recent evidence is beginning to suggest that a causal relationship may exist between the milk microbiota and host phenotype in mastitis. Multi-omic approaches can be leveraged to gain a mechanistic, molecular level understanding of how the milk microbiome might modulate host physiology, thereby informing strategies to prevent and ameliorate mastitis. In this paper, we review existing studies that have utilized omics approaches to investigate the role of the milk microbiome in mastitis. We also summarize the strengths and challenges associated with the different omics techniques including metagenomics, metatranscriptomics, metaproteomics, metabolomics and lipidomics and provide perspective on the integration of multiple omics technologies for a better functional understanding of the milk microbiome.

Identification markers of goat milk adulterated with bovine milk based on proteomics and metabolomics

This study investigated the differences in proteins and metabolites from goat and bovine milk, and their mixtures, using data-independent-acquisition-based proteomics and metabolomics methods. In the skim milk, relative abundances of secretoglobin family 1D member (SCGB1D), polymeric immunoglobulin receptor, and glycosylation-dependent cell adhesion molecule 1 were increased, with an increase in the amount of 1-100 % bovine milk and served as markers at the 1 % adulteration level. In whey samples, β-lactoglobulin and α-2-HS-glycoprotein could be used to detect adulteration at the 0.1 % adulteration level, and SCGB1D and zinc-alpha-2-glycoprotein at the 1 % level. The metabolites of uric acid and N-formylkynurenine could be used to detect bovine milk at adulteration levels as low as 1 % based on variable importance at a projection value of > 1.0 and P-value of < 0.05. Our findings suggest novel markers of SCGB1D, uric acid, and N-formylkynurenine that can help to facilitate assessments of goat milk authenticity.

Influence of maternal body mass index on human milk composition and associations to infant metabolism and gut colonisation: MAINHEALTH - a study protocol for an observational birth cohort

INTRODUCTION

Human milk provides all macronutrients for growth, bioactive compounds, micro-organisms and immunological components, which potentially interacts with and primes infant growth and, development, immune responses and the gut microbiota of the new-born. Infants with an overweight mother are more likely to become overweight later in life and overweight has been related to the gut microbiome. Therefore, it is important to investigate the mother-milk-infant triad as a biological system and if the maternal weight status influences the human milk composition, infant metabolism and gut microbiome.

METHODS AND ANALYSIS

This study aims to include 200 mother-infant dyads stratified into one of three body mass index (BMI) categories based on mother's prepregnancy BMI. Multiomics analyses include metabolomics, proteomics, glycomics and microbiomics methods, aiming to characterise human milk from the mothers and further relate the composition to infant gut microbiota and its metabolic impact in the infant. Infant gut microbiota is analysed using 16S sequencing of faeces samples. Nuclear magnetic resonance and mass spectrometry are used for the remaining omics analysis. We investigate whether maternal pre-pregnancy BMI results in a distinct human milk composition that potentially affects the initial priming of the infant's gut environment and metabolism early in life.

ETHICS AND DISSEMINATION

The Central Denmark Region Committees on Health Research Ethics has approved the protocol (J-nr. 1-10-72-296-18). All participants have before inclusion signed informed consent and deputy informed consent in accordance with the Declaration of Helsinki II. Results will be disseminated to health professionals including paediatricians, research community, nutritional policymakers, industry and finally the public. The scientific community will be informed via peer-reviewed publications and presentations at scientific conferences, the industry will be invited for meetings, and the public will be informed via reports in science magazines and the general press. Data cleared for personal data, will be deposited at public data repositories.

TRIAL REGISTRATION NUMBER

Danish regional committee of the Central Jutland Region, journal number: 1-10-72-296-18, version 6.Danish Data Protection Agency, journal number: 2016-051-000001, 1304.

CLINICALTRIALS

gov, identifier: NCT05111990.

Changes in plasma fatty acids profile in hyperketonemic ewes during early lactation: a preliminary study

The transition from late pregnancy to early lactation is characterized by marked changes in energy balance of dairy ruminants. The mobilization of adipose tissue led to an increase in plasma non-esterified fatty acids (NEFA) and β-hydroxybutyrate (BHB). The aim of this study was to analyze the total plasma fatty acids of healthy and hyperketonemic dairy ewes in early lactation through gas chromatography (GC) to evaluate metabolic alterations. An observational study was used with a cross-sectional experimental design. Forty-six Sarda dairy ewes were enrolled in the immediate post-partum (7 ± 3 days in milk) and divided into two groups according to serum BHB concentration: non-hyperketonemic group (n = 28; BHB < 0.86 mmol/L) and hyperketonemic group (n = 18; BHB ≥ 0.86 mmol/L). A two-way ANOVA included the effect of group and parity was used to evaluate differences in fatty acids (FA) concentrations. A total of 34 plasma FA was assessed using GC. 12 out of 34 FA showed a significant different between groups and 3 out of 34 were tended to significance. Only NEFA concentration and stearic acid were influenced by parity. The results may suggest possible links with lipid metabolism, inflammatory and immune responses in hyperketonemic group. In conclusion, GC represents a useful tool in the study of hyperketonemia and primiparous dairy ewes might show a greater risk to develop this condition.

Effects of acute intravenous lipopolysaccharide administration on the plasma lipidome and metabolome in lactating Holstein cows experiencing hyperlipidemia

INTRODUCTION

The effects of lipopolysaccharides (i.e., endotoxin; LPS) on metabolism are poorly defined in lactating dairy cattle experiencing hyperlipidemia.

OBJECTIVES

Our objective was to explore the effects of acute intravenous LPS administration on metabolism in late-lactation Holstein cows experiencing hyperlipidemia induced by intravenous triglyceride infusion and feed restriction.

METHODS

Ten non-pregnant lactating Holstein cows (273 ± 35 d in milk) were administered a single bolus of saline (3 mL of saline; n [Formula: see text] 5) or LPS (0.375 [Formula: see text]g of LPS/kg of body weight; n [Formula: see text] 5). Simultaneously, cows were intravenously infused a triglyceride emulsion and feed restricted for 16 h to induce hyperlipidemia in an attempt to model the periparturient period. Blood was sampled at routine intervals. Changes in circulating total fatty acid concentrations and inflammatory parameters were measured. Plasma samples were analyzed using untargeted lipidomics and metabolomics.

RESULTS

Endotoxin increased circulating serum amyloid A, LPS-binding protein, and cortisol concentrations. Endotoxin administration decreased plasma lysophosphatidylcholine (LPC) concentrations and increased select plasma ceramide concentrations. These outcomes suggest modulation of the immune response and insulin action. Lipopolysaccharide decreased the ratio of phosphatidylcholine to phosphatidylethanomanine, which potentially indicate a decrease in the hepatic activation of phosphatidylethanolamine N-methyltransferase and triglyceride export. Endotoxin administration also increased plasma concentrations of pyruvic and lactic acids, and decreased plasma citric acid concentrations, which implicate the upregulation of glycolysis and downregulation of the citric acid cycle (i.e., the Warburg effect), potentially in leukocytes.

CONCLUSION

Acute intravenous LPS administration decreased circulating LPC concentrations, modified ceramide and glycerophospholipid concentrations, and influenced intermediary metabolism in dairy cows experiencing hyperlipidemia.

Effect of Supplementing Dairy Goat Diets With Rapeseed Oil or Sunflower Oil on Performance, Milk Composition, Milk Fatty Acid Profile, and in vitro Fermentation Kinetics

The aim of this study was to determine the effect of supplementing dairy goat diets with rapeseed oil and sunflower oil on performance, milk composition, milk fatty acid profile, and in vitro fermentation kinetics. Nine Danish Landrace goats with 42 ± 5 days in milk were allocated to three treatment groups for 42 days. Animals received a basal diet, formulated with 85:15 forage:concentrate ratio, and the basal diet was supplemented with either rapeseed oil or sunflower oil at 4% of dry matter. Goat milk was sampled on days 14, 21, and 42. Milk composition was similar between treatments. From day 14 to day 42, milk yield increased (1.03 vs. 1.34 kg/d), while milk fat (2.72 vs. 1.82 g/d) and total solids (11.2 vs. 9.14 %) were reduced. Compared to control and rapeseed oil, sunflower decreased (P &lt; 0.05) C4:0 (1.56, and 1.67 vs. 1.36 g/100 g) and both oils decreased (P &lt; 0.05) C18:3n3 (0.60 vs. 0.20 and 0.10 g/100g). Rapeseed oil increased (P &lt; 0.05) C18:2 cis9, trans11 compared to control and sunflower oil (0.37 vs. 0.13 and 0.19 g/100 g). Untargeted milk foodomics revealed slightly elevated (P &lt; 0.05) gluconic acid and decreased hippuric acid (P &lt; 0.05) in the milk of oil-fed goats compared to control. In vitro dry matter degradation (63.2 ± 0.02 %) was not affected by dietary treatments, while individual volatile fatty acid proportions, total volatile fatty acids (35.7 ± 2.44 mmol/l), CO2 (18.6 ± 1.15 mol), and CH4 (11.6 ± 1.16 mol) were not affected by dietary treatments. Sunflower oil and rapeseed oil decreased (P &lt; 0.05) total gas production at 24 and 48 h compared with control. Overall, the use of sunflower oil or rapeseed oil at 4% DM inclusion did not compromise animal performance and milk composition.

Exploring Human Milk Dynamics: Interindividual Variation in Milk Proteome, Peptidome, and Metabolome

Human milk is a dynamic biofluid, and its detailed composition receives increasing attention. While most studies focus on changes over time or differences between maternal characteristics, interindividual variation receives little attention. Nevertheless, a comprehensive insight into this can help interpret human milk studies and help human milk banks provide targeted milk for recipients. This study aimed to map interindividual variation in the human milk proteome, peptidome, and metabolome and to investigate possible explanations for this variation. A set of 286 milk samples was collected from 29 mothers in the third month postpartum. Samples were pooled per mother, and proteins, peptides, and metabolites were analyzed. A substantial coefficient of variation (>100%) was observed for 4.6% and 36.2% of the proteins and peptides, respectively. In addition, using weighted correlation network analysis (WGCNA), 5 protein and 11 peptide clusters were obtained, showing distinct characteristics. With this, several associations were found between the different data sets and with specific sample characteristics. This study provides insight into the dynamics of human milk protein, peptide, and metabolite composition. In addition, it will support future studies that evaluate the effect size of a parameter of interest by enabling a comparison with natural variability.

Immunometabolic response in Egyptian water buffalo cows during the transition period

Background and Aim:

The transition period is extremely critical for pregnant producing animals. However, there is very limited research on the metabolic and immunological changes in Egyptian water buffalo cows during the transition period. Therefore, this study was conducted to investigate the immunometabolic changes occurring during the transition period in Egyptian water buffalo cows.

Materials and Methods:

A total of 50 multiparous pregnant Egyptian water buffalo cows were subjected to weekly blood sampling 3 weeks before calving and 3 weeks after calving and on the day of parturition to determine the complete blood count, including red blood cell count, total leukocyte count (TLC), differential leukocyte count, hemoglobin level, and packed cell volume (PCV). Some selected serum biochemical and immunological parameters were analyzed, including serum glucose, beta-hydroxybutyric acid (BHBA), non-esterified fatty acids, triglycerides, high-density lipoprotein, low-density lipoprotein (LDL), very LDL (VLDL), cholesterol, total protein, albumin, globulin, creatinine, blood urea nitrogen (BUN), aspartate aminotransferase, alkaline phosphatase, alanine transaminase, gamma-glutamyl transferase, Haptoglobin, and C-reactive protein and the pro-inflammatory cytokines interleukin β1, interleukin 6 (IL-6), and tumor necrosis factor-alpha. All data were statistically analyzed using the IBM Statistical Package for the Social Sciences statistics software.

Results:

The neutrophil count showed a statistically significant increase at 2 weeks preparturition. There was also a significant increase in PCV, TLC, neutrophil count, and IL-6 and TNF-a level at the time of parturition and even at 2 weeks post parturition, except PCV that returned to normal levels in the 1^st week post parturition. BHBA and BUN levels were increased significantly in the 2^nd and 3^rd weeks postcalving. Serum creatinine and VLDL levels were decreased significantly at the time of parturition, and VLDL levels showed a significant decrease even till the 3^rd week postcalving, whereas creatinine levels gradually returned to the pre-calving levels in the 3^rd week postcalving. Other parameters showed no significant changes.

Conclusion:

The most important immunometabolic changes occur in the first 2 weeks post parturition in Egyptian water buffalo cows, which exhibit a potent, remarkable physiological adaptation achieved by their functional liver, which can help the animal overcome the stressful conditions during the transition period.

Integrated Metabolomics and Proteomics Dynamics of Serum Samples Reveals Dietary Zeolite Clinoptilolite Supplementation Restores Energy Balance in High Yielding Dairy Cows

Dairy cows can suffer from a negative energy balance (NEB) during their transition from the dry period to early lactation, which can increase the risk of postpartum diseases such as clinical ketosis, mastitis, and fatty liver. Zeolite clinoptilolite (CPL), due to its ion-exchange property, has often been used to treat NEB in animals. However, limited information is available on the dynamics of global metabolomics and proteomic profiles in serum that could provide a better understanding of the associated altered biological pathways in response to CPL. Thus, in the present study, a total 64 serum samples were collected from 8 control and 8 CPL-treated cows at different time points in the prepartum and postpartum stages. Labelled proteomics and untargeted metabolomics resulted in identification of 64 and 21 differentially expressed proteins and metabolites, respectively, which appear to play key roles in restoring energy balance (EB) after CPL supplementation. Joint pathway and interaction analysis revealed cross-talks among valproic acid, leucic acid, glycerol, fibronectin, and kinninogen-1, which could be responsible for restoring NEB. By using a global proteomics and metabolomics strategy, the present study concluded that CPL supplementation could lower NEB in just a few weeks, and explained the possible underlying pathways employed by CPL.

Changes in the Spectrum of Free Fatty Acids in Blood Serum of Dairy Cows during a Prolonged Summer Heat Wave

Simple Summary

Heat stress leads to poor welfare, decreased productivity, and poor product quality. It is known that the content of fatty acids in the blood can reflect the physiological state of the body under normal and pathological conditions. They can be biomarkers for the state of biomembranes associated with inflammation and indicate the state of energy imbalance during chronic heat stress. They perform various functions in the body; therefore, the determination of the spectrum of free fatty acids can be used as biomarkers of these processes. The changes in the spectrum of free fatty acids in the blood serum of dairy cows revealed in our study will make it possible to better understand the physiological state of the organism and possibly indicate ways to maintain the health and milk productivity of animals under conditions of prolonged hyperthermia.

Abstract

This experiment was conducted to study the effect of a prolonged hot period on the fatty acid (FA) composition in blood serum of dairy cows. Eighteen multiparous Holstein cows were randomly assigned to the hyperthermia group (HYP, n = 8) in August (summer season) and the control group (CON, n = 10) in October (autumn season). Blood from animals of the HYP group was collected in one heat wave, which was preceded by a long period of heat stress (HS, temperature-humidity index (THI ≥ 72)). Blood from cows of the CON group was collected under thermal comfort conditions (THI < 68). The spectrum of free fatty acids (FFA) in the blood serum was analyzed by gas chromatography. The concentration of FFA increased, including saturated FAs and monounsaturated FAs, in the blood serum of cows under conditions of prolonged HS. This was associated with the mobilization of FA into the bloodstream from adipose tissue, as a consequence of negative energy balance. An increase in the ratio of n-6/n-3 polyunsaturated FAs may indicate biomembrane dysfunction and adversely affect dairy cows. This study showed that prolonged periods of heat can affect the FA composition of blood. How much this leads to changes in the FA composition of milk and the quality of food products remains to be seen in further research.

Overview of Metabolomic Analysis and the Integration with Multi-Omics for Economic Traits in Cattle

Metabolomics has been applied to measure the dynamic metabolic responses, to understand the systematic biological networks, to reveal the potential genetic architecture, etc., for human diseases and livestock traits. For example, the current published results include the detected relevant candidate metabolites, identified metabolic pathways, potential systematic networks, etc., for different cattle traits that can be applied for further metabolomic and integrated omics studies. Therefore, summarizing the applications of metabolomics for economic traits is required in cattle. We here provide a comprehensive review about metabolomic analysis and its integration with other omics in five aspects: (1) characterization of the metabolomic profile of cattle; (2) metabolomic applications in cattle; (3) integrated metabolomic analysis with other omics; (4) methods and tools in metabolomic analysis; and (5) further potentialities. The review aims to investigate the existing metabolomic studies by highlighting the results in cattle, integrated with other omics studies, to understand the metabolic mechanisms underlying the economic traits and to provide useful information for further research and practical breeding programs in cattle.

Variation in milk fat globule size and composition: A source of bioactives for human health

Milk fat globules (MFGs) are secreted from the mammalian gland and are composed of a triacylglycerol core surrounded by a triple membrane structure, the milk fat globule membrane (MFGM). The MFGM contains complex lipids and proteins reported to have nutritional, immunological, neurological and digestive functions. Human and ruminant milk are shown to share a similar MFG structure but with different size, profile and abundance of protein and polar lipids. This review summarizes the reported data on human, bovine, caprine and ovine MFG composition and concentration of bioactive components in different MFG-size fractions. A comprehensive understanding of compositional variations between milk from different species and MFG size fractions may help promote various milk sources as targeted supplements to improve human development and health. MFG size and MFGM composition are species-specific and affected by lactation, diet and breed (or maternal origin). Purification and enrichment methods for some bioactive proteins and lipids present in the MFGM have yet to be established or are not scaled sufficiently to be used to supplement human diets. To overcome this problem, MFG size selection through fractionation or herd selection may provide a convenient way to pre-enrich the MFG fraction with specific protein and lipid components to fulfill human dietary and health requirements.

Milk Fatty Acids Composition Changes According to β-Hydroxybutyrate Concentrations in Ewes during Early Lactation

Simple Summary

Ketosis can occur during the last six weeks of gestation and continue to the early weeks of lactation due to an increase in energy requirement. This condition can cause substantial economic issues because of the decrease in production, the cost of medical management, the loss of the mothers and the lambs. A better knowledge of this disorder and its early diagnosis could make treatment more effective and optimize productivity. The aims of this study were to understand the metabolic status of the early-lactating ewes and to identify biomarkers for precocious diagnosis of subclinical ketosis using gas chromatographic technique. Different relationships were found between milk fatty acids and metabolic status of the ewes. Furthermore, 8 potential biomarkers were determined.

Abstract

Ketosis is a metabolic disease of pregnant and lactating ewes linked to a negative energy balance which can cause different economic losses. The aims of this study were to understand the metabolic status of the early-lactating ewes and to identify biomarkers for early diagnosis of subclinical ketosis. Forty-six Sarda ewes were selected in the immediate post-partum for the collection of the biological samples. A blood sample from the jugular vein was used to determine β-Hydroxybutyrate (BHB) concentrations. Animals were divided into two groups: BHB 0 or healthy group (n = 28) with BHB concentration < 0.86 mmol/L; and BHB 1 or subclinical ketosis (n = 18) with a BHB concentration ≥ 0.86 mmol/L. Ten mL of pool milk were collected at the morning milking for the analyses. The concentration of 34 milk fatty acids was evaluated using gas chromatography. Two biochemical parameters and 11 milk fatty acids of the total lipid fraction presented a p-value ≤ 0.05. The study revealed different relationships with tricarboxylic acid cycle, blood flows, immune and nervous systems, cell functions, inflammatory response, and oxidative stress status. Eight parameters were significant for the receiver operating characteristic (ROC) analysis with an area under the curve greater than 0.70.

Comparison of Metabolic Alterations in Serum and Milk Whey Between Inactive Ovaries and Estrus Dairy Cows

Inactive ovaries (IOs) affect the estrus cycle and timed artificial insemination (TAI) efficiency in dairy cows during early lactation. The objective of the experiment was to determine metabolic changes in the serum and milk whey of dairy cows with IO and estrus. Twenty-eight healthy postpartum Holstein cows in similar age, milk production, and body condition were selected at 30 days postpartum for tracking to 70 days postpartum, and estrus performance was recorded through Afi Farm® software. The ovarian status and follicular diameter of dairy cows were examined by an experienced breeder through B-ultrasound and rectal examination. Fourteen normal estrus cows were allocated to control group A and 14 cows with IO to group B, all at 30–70 days postpartum. The serum and milk whey in the two groups of cows at 70 days postpartum were used for non-targeted nuclear magnetic resonance (¹H-NMR) analysis to measure the different metabolites of cows with IO. In group B compared with group A at 70 days postpartum, there was an increase in the milk whey of six different metabolites including succinate, creatine phosphate, glycine, myo-inositol, glycolate, and orotate and a decrease in the milk whey of seven metabolites, including alanine, creatinine, o-phosphorylcholine, lactose, taurine, galactose, and glucose-1-phosphate. There was an increase in the serum of group B cows of four differential metabolites, including 3-hydroxybutyrate, acetate, glutamine, and glycine and a decrease in the serum of nine differential metabolites, including alanine, succinate, citrate, creatinine, o-phosphocholine, glucose, myo-inositol, tyrosine, and histidine compared with group A. Group B cows with IO had decreased glucose metabolism and impaired tricarboxylic acid cycle, increased lipid mobilization, and abnormal amino acid metabolism. The study provides a potential prevention strategy for IO in dairy cows in future.

Metabolomics of Milk Reflects a Negative Energy Balance in Cows

Dairy cows can experience a negative energy balance (NEB) in early lactation when feed intake is too low to meet the energy requirements for body maintenance and milk production. Metabolic changes occur in mammary gland cells of animals experiencing a negative energy balance. We studied these metabolic changes in milk samples from dairy cows in relation to energy balance status using liquid chromatography–mass spectrometry (QQQ-LC–MS) and nuclear magnetic resonance (¹H NMR). NMR and LC–MS techniques are complementary techniques that enabled a comprehensive overview of milk metabolites in our study. Energy balance and milk samples were obtained from 87 dairy cows. A total of 55 milk metabolites were reliably detected, of which 15 metabolites were positively correlated to energy balance and 20 were negatively correlated to energy balance. Cows in NEB produced more milk with increased milk fat yield and higher concentrations of citrate, cis-aconitate, creatinine, glycine, phosphocreatine, galactose-1-phosphate, glucose-1-phosphate, UDP-N-acetyl-galactosamine, UDP-N-acetyl-glucosamine, and phosphocholine but lower concentrations of choline, ethanolamine, fucose, N-acetyl-neuraminic acid, N-acetyl-glucosamine, and N-acetyl-galactosamine. During NEB, we observed an increased leakage of cellular content, increased synthesis of nucleic acids and cell membrane phospholipids, an increase in one-carbon metabolic processes, and an increase in lipid-triglyceride anabolism. Overall, both apoptosis combined with cellular renewal is paramount in the mammary gland in cows in NEB.

Staphylococcus aureus-induced proteomic changes in the mammary tissue of rats: A TMT-based study

Staphylococcus aureus is one of the most important pathogens causing mastitis in dairy cows. The objective of this study was to establish a rat model of mastitis induced by S. aureus infection and to explore changes in the proteomes of mammary tissue in different udder states, providing a better understanding of the host immune response to S. aureus mastitis. On day 3 post-partum, 6 rats were randomly divided into two groups (n = 3), with either 100 μL of PBS (blank group) or a S. aureus suspension containing 2×10⁷ CFU·mL⁻¹ (challenge group) infused into the mammary gland duct. After 24 h of infection, the rats were sacrificed, and mammary gland tissue was collected. Tandem mass tag (TMT)-based technology was applied to compare the proteomes of healthy and mastitic mammary tissues. Compared with the control group, the challenge group had 555 proteins with significant differences in expression, of which 428 were significantly upregulated (FC>1.2 and p<0.05) and 127 were downregulated (FC>0.83 and p<0.05 or p<0.01). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses revealed that upregulated differentially significant expressed proteins (DSEPs) were associated with mainly immune responses, including integrin alpha M, inter-α-trypsin inhibitor heavy chain 4, and alpha-2-macroglobulin. This study is the first in which a rat model of S. aureus-induced mastitis was used to explore the proteins related to mastitis in dairy cows by TMT technology, providing a model for replication of dairy cow S. aureus-induced mastitis experiments.

Relationship between energy balance and metabolic profiles in plasma and milk of dairy cows in early lactation

Negative energy balance in dairy cows in early lactation is related to alteration of metabolic status. However, the relationships among energy balance, metabolic profile in plasma, and metabolic profile in milk have not been reported. In this study our aims were: (1) to reveal the metabolic profiles of plasma and milk by integrating results from nuclear magnetic resonance (NMR) with data from liquid chromatography triple quadrupole mass spectrometry (LC-MS); and (2) to investigate the relationship between energy balance and the metabolic profiles of plasma and milk. For this study 24 individual dairy cows (parity 2.5 ± 0.5; mean ± standard deviation) were studied in lactation wk 2. Body weight (mean ± standard deviation; 627.4 ± 56.4 kg) and milk yield (28.1 ± 6.7 kg/d; mean ± standard deviation) were monitored daily. Milk composition (fat, protein, and lactose) and net energy balance were calculated. Plasma and milk samples were collected and analyzed using LC-MS and NMR. From all plasma metabolites measured, 27 were correlated with energy balance. These plasma metabolites were related to body reserve mobilization from body fat, muscle, and bone; increased blood flow; and gluconeogenesis. From all milk metabolites measured, 30 were correlated with energy balance. These milk metabolites were related to cell apoptosis and cell proliferation. Nine metabolites detected in both plasma and milk were correlated with each other and with energy balance. These metabolites were mainly related to hyperketonemia; β-oxidation of fatty acids; and one-carbon metabolism. The metabolic profiles of plasma and milk provide an in-depth insight into the physiological pathways of dairy cows in negative energy balance in early lactation. In addition to the classical indicators for energy balance (e.g., β-hydroxybutyrate, acetone, and glucose), the current study presents some new metabolites (e.g., glycine in plasma and milk; kynurenine, panthothenate, or arginine in plasma) in lactating dairy cows that are related to energy balance and may be of interest as new indicators for energy balance.

Identification of disordered metabolic networks in postpartum dairy cows with left displacement of the abomasum through integrated metabolomics and pathway analyses

High-producing dairy cows are easily affected by left displacement of the abomasum (LDA) within 4 weeks postpartum. Although LDA is highly associated with metabolic disturbances, the related information on comprehensive metabolic changes, with the exception of some blood biochemical parameters, remains limited. In this study, the changes in plasma metabolites and in the metabolic profile of postpartum dairy cows with LDA were investigated through liquid chromatography coupled with quadrupole time of flight mass spectrometry (LC-Q/TOF-MS)-based metabolomics, and the metabolic networks related to LDA were constructed through metabolomics pathway analysis (MetPA). An obvious change in the metabolic profile was reflected by significant variations in 68 plasma metabolites in postpartum dairy cows with LDA, and these variations consequently altered 13 metabolic pathways (histidine metabolism, tyrosine metabolism, valine, leucine and isoleucine biosynthesis, phenylalanine, tyrosine and tryptophan biosynthesis, arginine and proline metabolism, tryptophan metabolism, synthesis and degradation of ketone bodies, linoleic acid metabolism, arachidonic acid metabolism, citrate cycle, butanoate metabolism, vitamin B₆ metabolism and pyrimidine metabolism). This study shows that the more detailed information obtained by LC-Q/TOF-MS-based metabolomics and MetPA might contribute to a better understanding of the disordered metabolic networks in postpartum dairy cows with LDA.

Characterization of the colostrum and transition milk proteomes from primiparous and multiparous Holstein dairy cows

Colostrum plays a vital role in the nutrition, development, and immunity of a newborn calf. This study aimed to characterize the protein profile of colostrum and to identify changes in the colostrum proteome across parity during the transition to mature milk. Colostrum and transition milk samples were collected at milkings 1, 2, 4, and 14 after calving from multiparous (n = 10) and primiparous cows (n = 10). Samples were skimmed, fractionated, and enriched before analysis for low-abundance proteins by liquid chromatography-tandem mass spectroscopy (LC-MS/MS). Changes in protein abundances were analyzed using PROC MIXED in SAS (SAS Institute Inc., Cary, NC) with determination of the adaptive false discovery rate adjustment using a MULTTEST procedure to identify effects of parity (P), milking number (MN), and their interaction (MN×P). We identified 86 proteins through LC-MS/MS, including 3 low-abundance proteins that were affected by P, 78 that were affected by MN, and 36 affected by MN×P. Prominent ontological groupings of proteins affected by MN included defense or immunity proteins, such as immunoglobulins. Proteins involved in the plasminogen activating cascade and more broadly, blood coagulation, were affected by MN×P. The results of this study add to increasing knowledge of the colostrum and transition milk proteomes, and this is the first study to find evidence of different abundances of these proteins when examined across P, MN, and MN×P. These findings aid in the identification of potential milk protein biomarkers for mammary health during the early postpartum period.

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.

Short communication: Changes under low ambient temperatures in the milk lipodome and metabolome of mid-lactation cows after dehorning as a calf

Horns are living tissue and cows can use their horns for thermoregulatory purposes. We investigated the effect of the presence of horns on the metabolome of milk serum and lipidome of milk fat, to assess the physiological effect of dehorning. Milk sampling took place at low ambient temperatures of -6 to 2°C. Horned and dehorned cows were kept in a mixed herd of Holstein Friesian and Brown Swiss cows. The hypothesis was that horned cows needed to increase their metabolism to compensate for additional heat loss through the presence of their horns. No differences were observed in milk yield, milk solids, and somatic cell counts between horned and dehorned cows. For the milk metabolome, horned cows showed an upregulation of several glucogenic AA that could be transformed into glucose for energy supply and a downregulation of sugar intermediates and γ-glutamylcysteine compared with dehorned cows. The fatty acid (FA) composition in horned cows showed a shift toward decreased odd medium-chain FA (C7:0, C9:0, and C11:0) and increased cis-vaccenic acid (C18:1n-7 cis-11) and stearidonic acid (C18:4n-3). The changes in milk composition related to additional heat loss in horned cows indicate a competition in C3 metabolism for glucose synthesis and de novo FA synthesis under cold stress.

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

Identification and characterization of the comprehensive bovine milk proteome has historically been limited due to the dichotomy of protein abundances within milk. The high abundance of a select few proteins, including caseins, α-lactalbumin, β-lactoglobulin, and serum albumin, has hindered intensive identification and characterization of the vast array of low-abundance proteins in milk due to limitations in separation techniques and protein labeling capacity. In more recent years, the development and advancement of proteomics techniques have yielded valuable tools for characterization of the protein profile in bovine milk. More extensive fractionation and enrichment techniques, including the use of combinations of precipitation techniques, immunosorption, gel electrophoresis, chromatography, ultracentrifugation, and hexapeptide-based binding enrichment, have allowed for better isolation of lower abundance proteins for further downstream liquid chromatography-tandem mass spectrometry approaches. The different milk subfractions isolated during these processes can also be analyzed as individual entities to assess the protein profile unique to the different fractions-for instance, investigation of the skim milk-associated proteome versus the milk fat globule membrane-associated proteome. Updates to high-throughput methods, equipment, and software have also allowed for greater interpretation and visualization of the data. For instance, labeling techniques have enabled analysis of multiplexed samples and more accurate comparison of specific protein abundances and quantities across samples, and integration of gene ontology analysis has allowed for a more in-depth and visual representation of potential relationships between identified proteins. Inclusively, these developments in proteomic techniques have allowed for a rapid increase in the number of milk-associated proteins identified and a better grasp of the relationships and potential functionality of the proteins within the milk proteome.

Milk Metabolomics Data Reveal the Energy Balance of Individual Dairy Cows in Early Lactation

In early lactation, dairy cows typically have a negative energy balance which has been related to metabolic disorders, compromised health and fertility, and reduced productive lifespan. Assessment of the energy balance, however, is not easy on the farm. Our aims were to investigate the milk metabolic profiles of dairy cows in early lactation, and to obtain models to estimate energy balance from milk metabolomics data and milk production traits. Milk samples were collected in week 2 and 7 after calving from 31 dairy cows. For each cow, the energy balance was calculated from energy intake, milk production traits and body weight. A total of 52 milk metabolites were detected using LC-QQQ-MS. Data from different lactation weeks was analysed by partial least squares analysis, the top 15 most relevant variables from the metabolomics data related to energy balance were used to develop reduced linear models to estimate energy balance by forward selection regression. Milk fat yield, glycine, choline and carnitine were important variables to estimate energy balance (adjusted R²: 0.53 to 0.87, depending on the model). The relationship of these milk metabolites with energy balance is proposed to be related to their roles in cell renewal.

Evaluation of sample preparation methods for NMR-based metabolomics of cow milk

The quality of milk metabolome analyzed by nuclear magnetic resonance (NMR) is greatly influenced by the way samples are prepared. Although this analytical method is increasingly used to study milk metabolites, a thorough examination of available sample preparation protocols for milk has not been reported yet. We evaluated the performance of eight milk preparation methods namely (1) raw milk without any processing; (2) skimmed milk; (3) ultrafiltered milk; (4) skimming followed by ultrafiltration; (5) ultracentrifuged milk; (6) methanol; (7) dichloromethane; and (8) methanol/dichloromethane, in terms of spectra quality, repeatability, signal-to-noise ratio, extraction efficiency and yield criteria. A pooled sample of milk was used for all protocols. Skimming, ultracentrifugation and unprocessed milk protocols showed poor NMR spectra quality. Protocols involving multiple steps, namely methanol/dichloromethane extraction, and skimming followed by ultrafiltration produced inadequate results for signal-to-noise ratio parameter. Methanol and skimming associated to ultrafiltration provided good repeatability results compared to the other protocols. Chemical-based sample preparation protocols, particularly methanol, showed more efficient metabolite extraction compared to physical preparation methods. When considering all evaluation parameters, the methanol extraction protocol proved to be the best method. As a proof of utility, methanol protocol was then applied to milk samples from dairy cows fed a diet with or without a feed additive, showing a clear separation between the two groups of cows.

NMR metabolomic fingerprinting distinguishes milk from different farms

A fast and reproducible protocol for milk Nuclear Magnetic Resonance (NMR) metabolomic fingerprinting was developed, allowing for an accurate discrimination among milk samples from large-scale distribution, as well as among milk sample from different farms located in the same restricted geographical area. Seasonal variations in milk composition and correlations with cows' nutritional patterns are also assessed, underlining relationships between feeding and metabolites. The most important difference was related to the use of silage feeding. This finding is relevant to assess the suitability of milk for different dairy products. A prominent example is parmesan cheese, the preparation protocol of which excludes milk from silage-fed cows.

GLUT1 and lactose synthetase are critical genes for lactose synthesis in lactating sows

Background

Lactose synthesis rate is an important factor in milk production and quality in mammals. Understanding the lactose synthesis mechanism is crucial for the improvement of milk quantity and quality. However, research on the temporal gene changes regarding lactose synthesis during the whole lactation is still limited. The objective of this study was to determine gene expression profiles related to lactose synthesis in sows during lactation, and further identify the critical steps or key factors in the lactose synthesis pathway.

Methods

To determine the temporal change of factors related to lactose synthesis in sows, milk from eight multiparous Yorkshire sows (parity 3 to 6) was collected at 0 h, 2 h, 6 h, 12 h, 24 h, day 2, 3, 4, 7, 14, and 21 after birth of the first piglet. Lactose content, prolactin and progesterone concentration, and gene or protein expression related to lactose synthesis were measured.

Results

The lactose yield increased gradually from D2 to D21 and reached a maximum at D14 (3-fold from D2) during lactation (P < 0.05). A similar trend was observed in IGF-1 and insulin concentrations in milk, both of which were greatest at D3 with a subsequent decrease during middle to late lactation. Conversely, milk prolactin and progesterone concentrations moderately decreased with the progression of lactation. The mRNA or protein expressions related to glucose transportation (GLUT1), glucose-galactose interconversion (HK1 and UGP2), UDP-galactose transportation (SLC35A2), and lactose synthetase (LALBA and B4GALT1) in the lactose synthesis pathway were significantly upregulated during early to middle lactation and plateaued by late lactation (P < 0.05).

Conclusions

These novel findings suggest that the increased lactose synthesis in lactation was related to the coordinated upregulation of genes or enzymes in the lactose synthesis pathway, and glucose transportation (GLUT1) and lactose synthetase (LALBA and B4GALT1) might be the critical steps in the lactose synthesis pathway of sows during lactation.

Significant changes in ITIH4, AHSG, ORM1, and CD46 content in milk fat globule membrane proteins of ketotic dairy cows

High concentrations of non-esterified fatty acid (NEFA) and β-hydroxybutyrate (BHBA) in cows' blood caused by ketosis are associated with inflammatory states. We hypothesised that ketosis in postparturient dairy cows would result in altered levels on inflammation-related proteins not only in plasma but also in the milk fat globule membranes (MFGM). Thirty cows were selected from a dairy farm in Heilongjiang, China. Inflammatory milk fat globule membrane proteins were detected using ELISA kits, and a fully automatic biochemical analyser was used to measure the concentrations of BHBA, NEFA, glucose (GLU) and triglyceride (TG) in plasma. MFGM protein from milk of ketotic cows contained significantly different concentrations of acute-phase response proteins (complement C3 (C3), prothrombin (F2), alpha-1-acid glycoprotein (ORM1), inter-alpha-trypsin inhibitor heavy chain H4 (ITIH4), alpha-2-HS-glycoprotein (AHSG), complement C9 (C9), complement regulatory protein variant 4 (CD46)) in comparison with milk from non-ketotic cows. Blood concentrations of C3, complement C9 (C9), tumour necrosis factor α (TNFα), MFGM C3, monocyte differentiation antigen CD14 (CD14) and ORM1 levels were correlated with energy balance. ITIH4 and CD46 increased, and AHSG and ORM1 decreased before the onset of ketosis. These biomarkers offer potential as predictors and monitors of ketosis in at-risk cows.

The relationship between milk metabolome and methane emission of Holstein Friesian dairy cows: Metabolic interpretation and prediction potential

This study aimed to quantify the relationship between CH₄ emission and fatty acids, volatile metabolites, and nonvolatile metabolites in milk of dairy cows fed forage-based diets. Data from 6 studies were used, including 27 dietary treatments and 123 individual observations from lactating Holstein-Friesian cows. These dietary treatments covered a large range of forage-based diets, with different qualities and proportions of grass silage and corn silage. Methane emission was measured in climate respiration chambers and expressed as production (g per day), yield (g per kg of dry matter intake; DMI), and intensity (g per kg of fat- and protein-corrected milk; FPCM). Milk samples were analyzed for fatty acids by gas chromatography, for volatile metabolites by gas chromatography-mass spectrometry, and for nonvolatile metabolites by nuclear magnetic resonance. Dry matter intake was 15.9 ± 1.90 kg/d (mean ± SD), FPCM yield was 25.2 ± 4.57 kg/d, CH₄ production was 359 ± 51.1 g/d, CH₄ yield was 22.6 ± 2.31 g/kg of DMI, and CH₄ intensity was 14.5 ± 2.59 g/kg of FPCM. The results show that changes in individual milk metabolite concentrations can be related to the ruminal CH₄ production pathways. Several of these relationships were diet driven, whereas some were partly dependent on FPCM yield. Next, prediction models were developed and subsequently evaluated based on root mean square error of prediction (RMSEP), concordance correlation coefficient (CCC) analysis, and random 10-fold cross-validation. The best models with milk fatty acids (in g/100 g of fatty acids; MFA) alone predicted CH₄ production, yield, and intensity with a RMSEP of 34 g/d, 2.0 g/kg of DMI, and 1.7 g/kg of FPCM, and with a CCC of 0.67, 0.44, and 0.75, respectively. The CH₄ prediction potential of both volatile metabolites alone and nonvolatile metabolites alone was low, regardless of the unit of CH₄ emission, as evidenced by the low CCC values (<0.35). The best models combining the 3 types of metabolites as selection variables resulted in the inclusion of only MFA for CH₄ production and CH₄ yield. For CH₄ intensity, MFA, volatile metabolites, and nonvolatile metabolites were included in the prediction model. This resulted in a small improvement in prediction potential (CCC of 0.80; RMSEP of 1.5 g/kg of FPCM) relative to MFA alone. These results indicate that volatile and nonvolatile metabolites in milk contain some information to increase our understanding of enteric CH₄ production of dairy cows, but that it is not worthwhile to determine the volatile and nonvolatile metabolites in milk to estimate CH₄ emission of dairy cows. We conclude that MFA have moderate potential to predict CH₄ emission of dairy cattle fed forage-based diets, and that the models can aid in the effort to understand and mitigate CH₄ emissions of dairy cows.

Proteomics and metabolomics characterizing the pathophysiology of adaptive reactions to the metabolic challenges during the transition from late pregnancy to early lactation in dairy cows

The transition from late pregnancy to early lactation is a critical period in a dairy cow's life due to the rapidly increasing drain of nutrients from the maternal organism towards the foetus and into colostrum and milk. In order to cope with the challenges of parturition and lactation, comprehensive adaptive reactions comprising the endocrine and the immune system need to be accomplished. There is high variation in this coping ability and both metabolic and infectious diseases, summarized as "production diseases", such as hypocalcaemia (milk fever), fatty liver syndrome, laminitis and ketosis, may occur and impact welfare, productive lifespan and economic outcomes. Proteomics and metabolomics have emerged as valuable techniques to characterize proteins and metabolite assets from tissue and biological fluids, such as milk, blood and urine. In this review we provide an overview on metabolic status and physiological changes during the transition period and the related production diseases in dairy cows, and summarize the state of art on proteomics and metabolomics of biological fluids and tissues involved in metabolic stress during the peripartum period. We also provide a current and prospective view of the application of the recent achievements generated by omics for biomarker discovery and their potential in diagnosis.

BIOLOGICAL SIGNIFICANCE

For high-yielding dairy cows there are several "occupational diseases" that occur mainly during the metabolic challenges related to the transition from pregnancy to lactation. Such diseases and their sequelae form a major concern for dairy production, and often lead to early culling of animals. Beside the economical perspective, metabolic stress may severely influence animal welfare. There is a multitude of studies about the metabolic backgrounds of such so called production diseases like ketosis, fatty liver, or hypocalcaemia, although the investigations aiming to assess the complexity of the pathophysiological reactions are largely focused on gene expression, i.e. transcriptomics. For extending the knowledge towards the proteome and the metabolome, the respective technologies are of increasing importance and can provide an overall view of how dairy cows react to metabolic stress, which is needed for an in-depth understanding of the molecular mechanisms of the related diseases. We herein review the current findings from studies applying proteomics and metabolomics to transition-related diseases, including fatty liver, ketosis, endometritis, hypocalcaemia and laminitis. For each disease, a brief overview of the up to date knowledge about its pathogenesis is provided, followed by an insight into the most recent achievements on the proteome and metabolome of tissues and biological fluids, such as blood serum and urine, highlighting potential biomarkers. We believe that this review would help readers to be become more familiar with the recent progresses of molecular background of transition-related diseases thus encouraging research in this field.

NMR-metabolomics profiling of mammary gland secretory tissue and milk serum in two goat breeds with different levels of tolerance to seasonal weight loss

Goats are of special importance in the Mediterranean and tropical regions for producing a variety of dairy products. The scarcity of pastures during the dry season leads to seasonal weight loss (SWL), which affects milk production. In this work, we studied the effect of feed-restriction on two dairy goat breeds, with different tolerance levels to SWL: the Majorera breed (tolerant) and the Palmera breed (susceptible). Nuclear magnetic resonance (NMR) was used to compare the metabolome of an aqueous fraction of the mammary gland and milk serum from both breeds. Goats in mid-lactation were divided by breed, and each in two feed-regime groups: the control group and the restricted-fed group (to achieve 15-20% reduction of body weight at the end of the experiment). Milk and mammary gland samples were collected at the end of the experimental period (23rd day). (1)H NMR spectra were collected from the aqueous extract of the mammary gland biopsies and the milk serum. Profiling analysis has led to the identification of 46 metabolites in the aqueous extract of the mammary gland. Lactose, glutamate, glycine and lactate were found to be the most abundant. Analysis of milk serum allowed the identification of 50 metabolites, the most abundant being lactose, citrate and creatine. Significant differences were observed, in mammary gland biopsies and milk serum, between control and restricted-fed groups in both breeds, albeit with no differences between the breeds. Variations seem to be related to metabolism adaptation to the low-energy diet and are indicative of breed-specific microflora. Milk serum showed more metabolites varying between control and restricted groups, than the mammary gland. The Majorera breed also showed more variations than the Palmera breed in milk samples, which could be an indication of a prompt adaptation to SWL by the Majorera breed.