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Journal of Animal Science - Animal Physiology

Pattern of γ-glutamyl transferase activity in cow milk throughout lactation and relationships with metabolic conditions and milk composition1

 

This article in JAS

  1. Vol. 93 No. 8, p. 3891-3900
     
    Received: Feb 17, 2015
    Accepted: June 13, 2015
    Published: August 3, 2015


    2 Corresponding author(s): luigi.calamari@unicatt.it
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doi:10.2527/jas.2015-9022
  1. L. Calamari 2,
  2. L. Gobbi,
  3. F. Russo and
  4. F. Piccioli Cappelli
  1. Istituto di Zootecnica, Università Cattolica del Sacro Cuore, Via Emilia Parmense, 84, 29122 Piacenza, Italy

Abstract

The main objective of this experiment was to study the γ-glutamyl transferase (GGT) activity in milk during lactation and its relationship with metabolic status of dairy cows, milk yield, milk composition, and cheesemaking properties. The study was performed in a tied stall barn and involved 20 lactations from 12 healthy multiparous Italian Friesian dairy cows. During lactation starting at d 10, milk samples were collected weekly and analyzed for composition, somatic cells count, titratable acidity, and milk coagulation properties. The GGT activity was measured in defatted samples. Blood samples were collected weekly to assess biochemical indicators related to energy, protein, and mineral metabolism, markers of inflammation and some enzyme activities. The lactations of each cow were retrospectively categorized into 2 groups according to their milk GGT activity value through lactation. A median value of GGT activity in the milk of all lactations was calculated (3,045 U/L), and 10 lactations with lower GGT activity were classified as low while 10 lactations with greater GGT activity were classified as high. The average value of milk GGT activity during lactation was 3,863 and 3,024 U/L for high and low, respectively. The GGT activity decreased in early lactation and reached minimum values in the second month (3,289 and 2,355 U/L for high and low, respectively). Thereafter GGT activity increased progressively, reaching values in late lactation of 4,511 and 3,540 U/L in high and low, respectively. On average, milk yield was 40.81 and 42.76 kg/d in high and low, respectively, and a negative partial correlation with milk GGT activity was observed. A greater milk protein concentration was observed in high (3.39%) compared with low (3.18%), and a positive partial correlation with milk GGT activity was observed. Greater titratable acidity in high than that in low (3.75 vs. 3.45 degrees Soxhlet-Henkel/50 mL, respectively) was also observed. Plasma glucose was greater in cows of high than in low group, while plasma urea was lower in the high than in the low group. No relationship between plasma GGT and milk GGT activity was observed. Our results show an important effect of lactation stage on milk GGT activity. The individual effect observed from consecutive lactations and the relationship between milk GGT activity and milk protein concentration in healthy cows could open prospects for GGT as a future tool in improving milk protein content.



INTRODUCTION

The enzyme γ-glutamyl transferase (GGT) is 1 of about 70 naturally occurring enzymes identified in milk; it is a glycoprotein, and isoelectric focusing shows 12 isozymes, which differ in sialic acid content (Fox and Kelly, 2006b). The enzyme is associated with the membranes of a number of epithelial cells in the kidney, pancreas, and liver, and it functions in the regulation of cellular glutathione (GSH) concentrations and may be involved in the transport of AA from blood into the mammary tissue, via the γ-glutamyl cycle (Baumrucker and Pocius, 1978).

In milk, about 70% of GGT activity is found in the membrane material in skimmed milk, much higher than the activity associated with milk fat globule membranes (MFGM; Baumrucker, 1979). In dairy technology, milk GGT activity is used to evaluate the effectiveness of pasteurization since it is completely inactivated by heating at 78°C for 15 s (Fox and Kelly, 2006b). GGT activity in milk varies during lactation and is highest in colostrum compared with mature milk in cows (Hadorn et al., 1997; Ontsouka et al., 2003), ewes (Martini et al., 2013), and mares (Rieland et al., 1998). After the colostral phase, the activity of GGT is considered quite stable, but specific studies on its pattern of change throughout lactation are not available. In the lactocyte, GGT could be involved in the supply of AA, as the inhibition of GGT in acini isolated from ovine mammary tissue led to decreased milk protein synthesis (Johnston et al., 2004). This evidence suggests that GGT could play a role in milk protein synthesis. Understanding the mechanisms involved in the AA supply of the lactocyte and its regulation by GGT could identify a process for the manipulation of milk protein synthesis.

The aim of our research was to study the pattern of change of GGT activity in milk of dairy cows and its relationships with metabolic status and milk composition with particular regard to milk protein characteristics related to cheese-making properties.


MATERIALS AND METHODS

Animal and Management Conditions

Research protocol and animal care were in accordance with Directive 2010/63/EU (European Union, 2010) on the protection of animals used for scientific purposes.

The trial was performed on Italian Friesian dairy cows kept in a tie-stall at the experimental barn of the Università Cattolica del Sacro Cuore (Piacenza, Italy). Constant microclimatic (a temperature of around 20°C, relative humidity between 60 and 70%, 14 h of light, and 10 h of dark per d) and managerial conditions (operators, similar batches of feed, milking frequency, and working routine) were maintained throughout the study. Water was offered ad libitum. The forages (corn silage, dehydrated grass, and dehydrated alfalfa) were offered in 2 equal meals, once every 12 h (0730 and 1930 h). Concentrate was provided by auto feeder in 8 equal meals in the lactating period (1 every 3 h). After calving, the amount of concentrate was gradually increased in 0.25- to 0.50-kg/d increments until the amount reached 1 kg per 3 kg of milk yield. Diets were formulated to cover requirements according to the NRC (2001).

Overall, 30 lactations from 12 multiparous (average parity 3.28 ± 1.03; range 2 to 5) Italian Friesian dairy cows were examined. All cows were checked daily, and records of all health-related problems as well as trauma and pharmacological treatments that occurred throughout the trial were recorded. Cows with health problems as well as cows with clinical mastitis or high somatic cells count (more than 4 × 105/mL) throughout lactation were excluded. Milk and blood from 20 lactations were selected for the study, which included 12 cows: 3 consecutive lactations of 2 cows, 2 consecutive lactations of 4 cows, and 1 lactation of 6 cows.

Feed and Diet Sampling and Analyses

Representative samples of each feed were taken continuously during the study. Each bale of hay was sampled and samples were pooled separately for grass and alfalfa, corn silage was sampled monthly, and concentrate at every delivery. All feed samples were analized for moisture, fat, CP, crude fiber, NDF, ADF, ADL, starch, and ash content using standard procedures, and nutritive values were calculated according to NRC (2001). Individual daily feed intake was calculated during the whole experimental period, weighing each feed offered to cows and the refusals on the following day. The determined DM content and the chemical and nutritive characteristics of each feed were then applied to individual daily feed intake to calculate the chemical and nutritive characteristics of the rations (Table 1) as well as the DM and nutrient intakes. These data were utilized to calculate energy balance on a weekly basis. The energy availability from body changes was not considered in this calculation.


View Full Table | Close Full ViewTable 1.

Composition, chemical analysis, and nutritive value of diets fed to cows during lactation

 
Item 30–60 d, % of DM 120–150 d, % of DM 240–270 d, % of DM
Ingredient
    Corn silage 26.49 26.71 28.98
    Alfalfa hay 9.75 10.38 11.18
    Grass hay 8.14 10.02 9.92
    Commercial concentrate mix1 55.62 52.89 49.91
Nutrients and DMI
    DMI, kg/d 23.98 24.74 22.93
    Crude protein, % DM 15.28 15.05 14.38
    Starch, % DM 26.04 24.81 25.23
    NDF, % DM 34.12 35.31 34.35
    NDF from forage, % DM 20.70 22.46 22.89
1Composition on as-fed basis: 41% corn flour, 17% dried beet pulp, 13.4% soybean meal, 10% wheat bran, 5% sunflower meal, 4% sugar beet stillage, 3.1% Ca-soap of palm fatty acids, 2.2% potato protein flour, 1.3% limestone, 1.2% sodium bicarbonate, 0.9% dicalcium phosphate, 0.6% magnesium oxide, 0.3% sodium chloride.

Blood Sampling and Analyses

Blood samples were collected weekly, starting at 10 d and lasting until 270 d after parturition. Samples were collected in the morning, before the feed distribution, by venipuncture from the jugular vein using 10-mL Li-heparin-treated tubes (Vacuette containing 18 IU of Li-heparin/mL; Greiner Bio One, Kremsmünster, Austria). Samples were immediately cooled in ice-water after the collection.

A small amount of blood was used for hematocrit (packed cell volume, PCV) determination after high-speed centrifugation (15,000 × g for 10 min at room temperature) in a capillary tube. The remaining blood was centrifuged (3,500 × g for 16 min at 4°C), and the obtained plasma was separated into several aliquots and stored at −20°C until further analysis. Plasma metabolites were analyzed at 37°C by an automated clinical analyzer (ILAB 600; Instrumentation Laboratory, Lexington, MA). Commercial kits were used to measure the concentration of glucose, total cholesterol, urea, calcium, inorganic phosphorus, magnesium, total protein, albumin, and total bilirubin (Instrumentation Laboratory), and zinc (Wako Chemicals GmbH, Neuss, Germany). A potentiometric system, with specific electrodes, was employed to measure Na, K, and Cl concentrations. Kinetic analysis was adopted to determine the activities of alkaline phosphatase (AP, EC 3.1.3.1), aspartate aminotransferase (AST, EC 2.6.1.1), and GGT (EC 2.3.2.2) using commercial kits (Instrumentation Laboratory). Ceruloplasmin (Cp) and haptoglobin concentrations were determined with reagents prepared according to the method reported by Bertoni et al. (1998).

Milk Sampling and Analyses

Cows were milked twice a day at 0500 and at 1700 h throughout lactation, and milk yield of individual cows was recorded at each milking. Representative samples were collected weekly from a morning milking for measurement of fat, protein, and lactose content and titratable acidity using Fourier transform mid-infrared equipment (Milkoscan FT 120; Foss Electric, Hillerød, Denmark). Somatic cells count (SCC) was determined using an optofluorometric method using a Fossomatic 180 (Foss Electric). Milk coagulation properties (MCP) were also measured on fresh milk samples using a Formagraph (Foss Electric). The MCP parameters registered were the rennet coagulation time (RCT, min), the curd firming rate that indicates the time from RCT to a curd firmness of 20 mm (k20, min), and the curd firmness at 30 min after enzyme addition (a30). For this analysis, 10 mL of milk was heated to 35°C, and 200 μL of rennet (Hansen standard 160 with 80% chymosin and 20% pepsin; Pacovis Amrein AG, Bern, Switzerland) diluted to 1.6% (wt/wt) in distilled water was added to the milk at the start of the analysis to obtain 0.051 international milk clotting units (IMCU)/mL. A fraction of fresh milk samples was defatted (3,500 g × 15 min at 6°C) and stored at −20°C. In these samples, the GGT activity was measured by kinetic analysis at 405 nm using an ILAB 600 (Instrumentation Laboratory) at a temperature of 37°C. The final mixture contained 4 μL of defatted milk sample, 40 μL of Triton X-100 (3% vol/vol), and 150 μL of specific reagent (Instrumentation Laboratory).

Statistical Analysis

All analyses were performed using the statistical software package SAS 9.2 (SAS Inst. Inc., Cary, NC). Data were tested for non-normality by the Shapiro test (SAS Inst. Inc.). In case of non-normality, parameters were normalized by log or exponential transformation. Transformations were performed for plasma total bilirubin, haptoglobin, AST, AP, and plasma GGT.

The lactations of each cow were retrospectively categorized into 2 groups according to their average value through lactation of GGT activity in milk. A median value of GGT activity observed in the milk of all lactations was calculated (3,492 U/L). Then, the average value of GGT activity in milk observed in each lactation was compared with this median value: the lactations with lower GGT activity were classified as low (10 lactations with an average value of 3,024 U/L, a range of 2,737 to 3,514 U/L, and a median value of 3,124 U/L), and the lactations with greater GGT activity were classified as high (10 lactations with an average value of 3,862 U/L, a range of 3,652 to 4,624 U/L, and a median value of 3,955 U/L).

Milk yield, milk characteristics, and plasma indices were submitted to repeated measures variance analysis using a mixed model (MIXED procedure of SAS; SAS Inst. Inc.). The model included the effect of classification based on GGT activity in milk (low and high), days in milk (DIM), individual variability (within cow × classification based on GGT activity in milk), and the classification based on GGT activity of milk × DIM interaction. The analysis was performed using 3 covariance structures: autoregressive order 1, compound symmetry, and spatial power. These were ranked according to their Akaike and Schwarz Bayesian information criterion, with the one having the least information criterion eventually chosen (Littell et al., 1998). For each effect, least squares means were computed and preplanned pairwise comparisons (PDIFF option, SAS Inst. Inc.) were conducted when the F-test of one of the main factors (DIM, classification based on GGT activity of milk, and interaction) was P < 0.10. Statistical significance was designated as P < 0.05, and tendencies were declared at P < 0.10.

Milk yield and milk characteristics were also processed by principal components analysis (PCA). Pearson’s and partial correlations between GGT activity of milk and milk yield as well as plasma indices were calculated using the CORR and MANOVA procedures (SAS Inst. Inc.). Multiple linear regressions were also calculated using the GGT activity of milk as the dependent variable and milk yield, fat, and protein content as independent variables. These regressions were calculated on data in early (40 to 70 DIM), intermediate (140 to 160 DIM) and late (250 to 280 DIM) lactation.


RESULTS

Diet Characteristics

Table 1 shows the composition of diets fed to animals during the experiment and the relative chemical and nutritive values. The diets were based on corn silage representing on average 27% of DM; this percentage was slightly greater in mid-late than in early lactation. The percentage of concentrate in the diet was on average 53% of DM, with lower values in mid-late lactation. The crude protein content of the diet in early-midlactation was on average 15.2% and in late lactation was 14.3% of DM. The content of NDF was quite stable throughout lactation (on average 34.6% of DM), while the NDF from forages was lower in early lactation and greater in late lactation.

Milk Yield and Milk Characteristics

The descriptive statistics of milk characteristics are shown in Table 2. The milk yield and the main milk characteristics of the 2 groups of animals categorized according to their average GGT activity in milk are presented in Table 3.


View Full Table | Close Full ViewTable 2.

Descriptive statistics of main milk components and GGT activity

 
Item1 Mean SD Minimum Maximum Median
Fat, % wt/vol 3.95 0.54 1.94 5.43 3.91
Protein, % wt/vol 3.29 0.32 2.46 4.35 3.27
Lactose, % wt/vol 5.11 0.17 4.03 5.52 5.10
SCC, log (n/mL) 4.65 0.39 3.84 5.59 4.69
GGT, U/L 3,453 707 1,515 5,574 3,464
1GGT, γ-glutamyl transferase. Activity measured on defatted milk; SCC, somatic cell count.

View Full Table | Close Full ViewTable 3.

Milk yield and milk characteristics in cows categorized according to the average GGT activity of milk during lactation1

 
P-value3
Item High Low SEM2 Gr Gr × DIM
Milk yield, kg/d 40.81 42.76 1.7185 ns <0.001
Fat, % w/v 4.04 3.86 0.1247 ns ns
Protein, % w/v 3.39 3.18 0.0741 0.014 <0.001
Lactose, % w/v 5.11 5.09 0.0500 ns <0.001
Titratable acidity, °SH/50 mL 3.75 3.45 0.0852 0.022 0.0548
SCC, log(n/mL) 4.71 4.59 0.0870 ns ns
Rennet coagulation time, min 17.40 17.72 1.1659 ns ns
Curd firming rate, min 6.37 6.99 0.9408 ns 0.0016
Curd firmness, mm 28.56 25.24 2.7404 ns ns
GGT4, U/L 3,862.67 3024.02 100.5900 <0.001 ns
1High, cows with greater average GGT activity in milk during lactation (n = 10); low, cows with lower average GGT activity in milk during lactation (n = 10); GGT, γ-glutamyl transferase; SCC, somatic cells count.
2Greatest SEM.
3P-values: Gr is the group effect (high vs. low); ns, not significant; days in milk (DIM) was always significant.
4Measured on defatted milk.

The average activity of GGT in milk was 3,443 U/L. In both groups (high and low), it decreased reaching a nadir during the first 30 to 60 DIM (Fig. 1); afterward, it increased rapidly in both groups, showing higher values (P < 0.001) than that observed at 10 DIM between 90 and 120 DIM. An interaction between group and DIM was observed as a consequence of the variability observed during lactation and not to a different trend between the 2 groups through lactation. It was also observed that cows categorized in the high group remained in that group in all consecutive lactations (1 cow with 3 lactations and 2 cows with 2 lactations). The same situation was observed in the low group (1 cow with 3 lactations and 2 cows with 2 lactations).

Figure 1.
Figure 1.

Pattern of change during lactation of γ-glutamyl transferase (GGT) activity in the defatted milk of cows categorized according to the average GGT activity of defatted milk during lactation (line with empty circles: least squares means of cows with greater average GGT activity; lines with black triangles: least squares means of cows with lower average GGT activity). Vertical bars represent SEM. DIM, days in milk.

 

The milk yield and DMI (Fig. 2) showed similar trends during the lactation for both groups. A partial negative correlation was observed between GGT activity and milk yield (r = −0.35; P < 0.001). The DMI did not differ between the 2 groups and was on average 24.3 kg/d in the high group and 24.4 kg/d in the low group.

Figure 2.
Figure 2.

Pattern of change during lactation of milk yield (continuous line) and DMI (dotted line) of cows categorized according to the average γ-glutamyl transferase (GGT) activity of defatted milk during lactation (line with empty circles: least squares means of cows with greater average GGT activity; lines with black triangles: least squares means of cows with lower average GGT activity). Vertical bars represent SEM. DIM, days in milk.

 

Milk fat content was on average 3.95% and did not differ between groups (Fig. 3a). A partial correlation between GGT activity and fat content was observed (r = 0.35; P < 0.001). Milk protein concentration (Table 3, Fig. 3b) was on average 3.29%, with greater (P = 0.014) values in high than in low cows. A significant interaction between group and DIM was also observed. During lactation, the milk protein content was always greater in the high group than in the low group (Fig. 3b), with increased differences between high and low values as proteins increased with DIM. A partial positive correlation between GGT activity and protein content was observed (r = 0.39; P < 0.001). The lactose concentration did not differ between groups, and also the pattern of change throughout lactation was similar in high and low cows (Fig. 3c).

Figure 3.
Figure 3.

Pattern of change during lactation of milk fat (a), milk protein (b), and lactose (c) of cows categorized according to the average γ-glutamyl transferase (GGT) activity of defatted milk during lactation (line with empty circles: least squares means of cows with greater average GGT activity; lines with black triangles: least squares means of cows with lower average GGT activity). Vertical bars represent SEM. DIM, days in milk.

 

Somatic cell count did not differ between groups, and on average the values were low due to the exclusion of lactations where clinical mastitis was observed. A partial correlation between SCC and GGT activity was found (r = 0.27; P < 0.001).

Among the cheesemaking properties, the titratable acidity was greater (P = 0.02) in high cows than in low cows, and a significant interaction between group and DIM was observed. Furthermore, a partial correlation between titratable acidity and GGT activity was observed (r = 0.24; P < 0.001). The MCP did not differ significantly between groups, and only curd firming rate showed a group × DIM interaction.

The results obtained with multiple linear regressions using a model including GGT activity of milk as a dependent variable and milk yield, fat, and protein content as independent variables are shown in Table 4. In early lactation, the independent variables explained 47% of the GGT variability, and the effect of protein content was highly significant. In late lactation, the coefficient of determination was lower (0.16), and only the effect of milk yield was significant.


View Full Table | Close Full ViewTable 4.

Multiple regressions by using GGT activity of milk (U/L) as the dependent variable and milk yield and its fat and protein content as independent variables1

 
Item 40–70 DIM2 140–170 DIM 250–280 DIM
Regression
    n 66 64 53
    R2 0.47 0.24 0.16
    P-value <0.001 <0.001 0.013
    Independent variables
        Milk yield, kg/d
            Coefficient −15.32 −27.99 −41.06
            SE 9.29 13.15 15.22
            P-value 0.104 0.037 0.001
        Milk fat, %
            Coefficient 340.86 41.02 57.93
            SE 121.83 194.44 171.59
            P-value 0.0069 ns3 ns
        Milk protein, %
            Coefficient 1,523.65 613.59 394.90
            SE 316.34 287.87 543.65
            P-value <0.001 0.037 ns
1GGT, γ-glutamyl transferase. Activity measured on defatted milk.
2DIM, days in milk.
3ns, Not significant.

The main results from the PCA on milk yield, milk variables, and DIM showed that the first principal component (PC1) and the second principal component (PC2) explained 32.2% and 20.5% of the total variance, respectively. The score plot (Fig. 4a) shows a clear separation between high and low cows.

Figure 4.
Figure 4.

(a) Score plot of principal components analysis (PCA)-analyzed milk samples from the cows involved in the research (cows categorized according to the average γ-glutamyl transferase [GGT] activity of defatted milk during lactation: empty circles represent cows with greater average GGT activity; filled triangles represent cows with lower average GGT activity) using the first 2 principal components (PC1 and PC2). (b) Loading plot of the first 2 (PC1 and PC2) principal components (RCT, rennet coagulation time; k20, curd firming rate; a30, curd firmness; SH, titratable acidity). DIM, days in milk; MY, milk yield; SCC, somatic cell count.

 

Plasma Parameters

The variables that mainly contributed to this separation were protein content and DIM, which were positively associated with GGT activity and milk yield and negatively associated with GGT activity (Fig. 4b).

The plasma metabolites measured in this study and analyzed according to the GGT activity observed in milk are shown in Table 5. All plasma variables were affected by the physiological phase. Furthermore, for all plasma traits, except Ca, K, and Zn, there were significant group × DIM interactions.


View Full Table | Close Full ViewTable 5.

Metabolic profile of cows categorized according to the average GGT activity of milk during lactation1

 
P2
Item High Low SEM Gr Gr × DIM
PCV, L/L 0.28 0.29 0.0106 ns <0.0001
Glucose, mmol/L 4.16 4.03 0.0801 ns <0.0001
Total cholesterol, mmol/L 7.29 6.66 0.3922 ns <0.0001
Urea, mmol/L 4.66 5.23 0.3696 ns <0.0001
Ca, mmol/L 2.56 2.51 0.0486 ns ns
Inorganic P mmol/L 1.90 1.86 0.0856 ns 0.0008
Mg, mmol/L 1.09 1.12 0.0136 ns 0.0006
Na, mmol/L 143.20 143.26 0.5408 ns <0.0001
K, mmol/L 4.07 4.01 0.0498 ns ns
Cl, mmol/L 104.61 105.73 0.4889 ns 0.0108
Zn, μmol/L 13.65 12.25 0.6026 ns ns
Ceruloplasmin μmol/L 2.28 2.56 0.1798 ns <0.0001
Total protein, g/L 81.87 81.07 1.3223 ns <0.0001
Albumin, g/L 38.11 37.42 0.7672 ns <0.0001
Globulin, g/L 43.9 43.75 1.6162 ns 0.0013
Haptoglobin, g/L 0.12 0.09 0.0254 ns <0.0001
AST, U/L 83.10 104.58 5.3491 0.0169 <0.0001
GGT, U/L 3.46 3.46 2.6317 ns <0.0001
AP, U/L 31.38 31.52 3.5841 ns 0.0208
Total bilirubin, μmol/L 1.05 1.12 0.1229 ns <0.0001
1High, cows with greater average γ-glutamyl transferase (GGT) activity in milk during lactation (n = 10); Low, cows with lower average GGT activity in milk during lactation (n = 10). Activity measured on defatted milk. PCV, packed cell volume; AST, aspartate aminotransferase; AP, alkaline phosphatase.
2P values: Gr is the group effect (high vs. low); ns, not significant; days in milk (DIM) was always significant.

Among the plasma metabolites related to energy and protein metabolism, glucose was numerically greater in high than in low cows, and urea was numerically lower in high than in low cows. A significant interaction between group and DIM was observed for both metabolites. Glucose was greater in high than in low cows in early and in midlactation (Fig. 5a). Urea was lower in high than in low cows only in midlactation (Fig. 5b). A partial correlation between GGT activity of milk and plasma glucose was observed (r = 0.24; P < 0.001). A weak partial correlation between the GGT activity of milk and plasma urea was also observed (r = −0.15; P < 0.001).

Figure 5.
Figure 5.

Pattern of change during lactation of plasma glucose (a) and plasma urea (b) of cows categorized according to the average γ-glutamyl transferase (GGT) activity of defatted milk during lactation (line with empty circles: least squares means of cows with greater average GGT activity; lines with black triangles: least squares means of cows with lower average GGT activity). Vertical bars represent SEM. DIM, days in milk.

 

Among plasma minerals, only Zn was numerically greater in high than in low cows, and a partial correlation between the GGT activity of milk and plasma Zn was observed (r = 0.31; P < 0.001). Among the inflammatory variables (i.e., positive and negative acute-phase proteins), a faster increase of albumin in the first month of lactation was observed in high compared with low cows (data not shown). The increase of total cholesterol after calving did not differ between groups, but at 60 DIM, greater values were reached in high than in low cows and remained greater in midlactation (data not shown).

Among enzyme activities, only plasma AST was greater in high than in low cows. Conversely, GGT activity observed in plasma of high cows did not differ from the value observed in low cows, and the plasma GGT activity was not correlated with the GGT activity observed in milk.


DISCUSSION

The MFGM and vesicle membranes are probably the source of most of the indigenous enzymes in milk (Shahani et al., 1973; Fox and Kelly, 2006a) and are a reflection of the cellular sources of these membranes, such as Golgi membranes, rough endoplasmic reticulum, and plasma membranes (Fox and Kelly, 2006b). Above 70% of the total GGT activity in milk was observed in skim milk, and above 40% of the total activity was linked to membranes (Baumrucker, 1979). During milk storage, the MFGM surrounding the fat globule may be lost into the skim milk by vesiculations and fragmentation (Jensen and Clark, 1988). Consequently, the time elapsed from milk sampling at milking and milk analysis could influence the results of GGT activity in skim milk. In our study, the fresh samples were immediately centrifuged and the defatted milk stored at −20°C until analysis. This suggests that the data presented here should be minimally influenced by GGT activity from MFGM.

High variability in milk GGT activity was observed in this study and, in particular, a high interanimal variability. The average value of milk GGT activity was 3,863 U/L in the cows categorized to the high GGT group, but it was only 3,024 U/L in the low GGT group. In this study, 2 cows were monitored for 3 consecutive lactations each and 4 cows for 2 consecutive lactations each. These cows maintained the categorization in the same group (high or low) in all monitored lactations, which suggests an important individual effect on the level of milk GGT activity.

One of first studies on GGT activity in the mammary gland observed a similar activity per gram of wet weight of mammary tissues in cows and rats (Baumrucker and Pocius, 1978). More recently, it has been observed that the levels of enzymes in milk are affected by several factors, which include the stage of lactation, the metabolic activity of cells, and the hormonal, nutritional, and metabolic status of the producing animal (Silanikove et al., 2006).

Milk GGT Activity and Stage of Lactation

The effect of lactation phase was demonstrated mainly when colostrum was compared with mature milk, with enzyme activity in colostrum higher than in mature cow’s milk (Shahani et al., 1980; Hadorn et al., 1997; Ontsouka et al., 2003). Similar results were observed for GGT activity between colostrum and the mature milk of sheep (Martini et al., 2013) and mares (Rieland et al., 1998). After the colostral phase, GGT activity was found relatively constant throughout lactation (Martini et al., 2013; Piga et al., 2013). In the current study, which focused on the lactation stage excluding the colostral phase, a significant effect of DIM was observed. The pattern of change in GGT activity throughout lactation was related to milk yield. The maximum values of GGT activity were observed in late lactation; however, these values were much lower than the values shown in colostrum (Braun et al., 1982; Ontsouka et al., 2003). PCA analysis of our data showed that the GGT activity in milk was mainly related to milk yield and to lactation phase. The negative relationship between GGT activity and milk yield could be a consequence of a dilution effect. The positive relationship between GGT activity and DIM is probably related to the gradual apoptosis of the mammary gland that begins after milk yield peak, which in turn causes a progressive decline in milk yield (Wilde et al., 1999) and an increased permeability of mammary tissue. These conditions are, in general, favorable to an increase of enzymes in milk that arises either from blood plasma, through “leaky junctions” between mammary cells (Ontsouka et al., 2003), and from death secretory cells in which GGT activity is distributed throughout the cytoplasm (Pero et al., 2006). A positive partial correlation between GGT activity and SCC was observed in our study when cows with low SCC were included. In such conditions, most of the SCC arises from the parenchyma.

Milk GGT Activity and Milk Protein Content

Increased GGT activity in mammary tissue at parturition and in early lactation has been shown in sheep (Johnston et al., 2004) and in the rat (Pocius et al., 1980). Siegrist et al. (1990) observed very low GGT activity in the virgin-mammary gland of a mouse and a progressive increase during pregnancy. Pero et al. (2006) observed in buffalo mammary tissue higher GGT activity at 120 than at 180 d of lactation, and both were greater than the values observed in nonlactating animals. In the mammary tissue, GGT is localized on the outer surface of plasma membranes and seems to promote the absorption of some AA across alveolar cell membranes (Baumrucker and Pocius, 1978; Baumrucker, 1985). However, Bell and Bauman (2006) indicated that there is no evidence that active transport is a limiting factor for the mammary acquisition and utilization of circulating AA. On the other hand, it seems probable that the mammary gland could enhance AA uptake in response to the mammary metabolic demand for AA (Bequette et al., 2000; Bequette et al., 2001). In the current study, a positive relationship between GGT activity and milk protein concentration was observed and confirms the positive relationship observed in our previous research (Calamari et al., 2005). Also, Peli et al. (2001) observed in a multivariate analysis a positive relationship of GGT activity with that of milk protein concentration. GGT is implicated in the regulation of cellular GSH and seems to be involved in the transport of AA from blood into the mammary tissue via the γ-glutamyl cycle. A positive correlation with milk protein yield supports the earlier hypothesis of an involvement of GGT in the biosynthesis of milk proteins (Baumrucker and Pocius, 1978).

A confirmation of these findings can be seen in the work of Johnston et al. (2004), which demonstrated a significant reduction in milk protein synthesis in ovine-isolated mammary cells using acivicin, which was previously demonstrated to inhibit GGT activity (Stole et al., 1994), indicating that GGT plays an important role in milk protein production in the ruminant. On the other hand, the research performed by Lee et al. (1996) showed that oxoproline in the rat lactating mammary tissue is capable of stimulating AA transport from blood to mammary tissue. Oxoproline is an intermediate of the γ-glutamyl cycle. The γ-glutamyl AA, produced by the interaction between the AA and GSH catalyzed by GGT, could be the extracellular signals transported into the cells and converted to oxoproline, which could activate transport or the metabolism of AA by the gland (Lee et al., 1996).

Although γ-glutamyl has a high affinity for cysteine (Thompson and Meister, 1977), acivicin inhibition decreased dose-dependently the synthesis of different types of caseins by different amounts, including non-cysteine-containing proteins (Johnston et al., 2004). Thus, GGT may be responsible for providing a complement of AA for milk protein synthesis, and also its inhibition could increase synthesis of some casein over others. In our study, the concentration of milk protein fractions was not measured. However, some cheesemaking properties (titratable acidity and MCP) were measured, and these properties are affected by many factors, including protein content and casein composition (Bertoni et al., 2001, 2005). A positive relationship between GGT activity and titratable acidity was observed in this study. Among MCP, only curd firmness showed a weak and positive relationship with milk GGT activity. These relationships are at least in part a consequence of the positive correlation between milk GGT activity and milk protein concentration.

The increase in GGT activity as a consequence of up regulation of the γ-glutamyl cycle and the consequent improved AA transport through the cell membrane for synthesis of milk proteins could improve the synthesis of other protein in the mammary parenchyma. It is well known that some enzymes, such as xanthine oxidase and lactoperoxidase, are components of the mammary innate immune system. These enzymes play a major role as antimicrobial factors, which exert both specific and nonspecific bacteriostatic and bactericidal activity (Silanikove et al., 2006) and can be transferred from the mother to the neonate for its protection against infections. It could be speculated that the increase of GGT activity in cows with high SCC is related to the production of protein synthesis involved in the mammary innate immune system.

Milk GGT Activity and Energy and Protein Status

In the current study, a positive relationship between milk GGT activity and plasma glucose and a negative relationship between milk GGT activity and plasma urea were observed. The γ-glutamyl cycle appears to be extremely energy demanding, as it utilizes 3 ATP per AA transported (Baumrucker, 1985). In our previous study (Calamari et al., 2005), a lower milk GGT activity in the hot summer season was observed despite the lower milk yield in summer and the negative correlation between GGT activity and milk yield observed in that study. It is known that in heat stress DMI is reduced and the energy requirement for maintenance is increased, with consequent worsening of energy balance and that, in such situation, blood glucose is low, while urea increases due to gluconeogenesis from AA (Bernabucci et al., 2010; Calamari et al., 2013). These findings seem to suggest relationships between energy metabolism and GGT activity in the mammary gland. These could influence protein synthesis, as well as protein composition, with possible implications for cheese-making properties related to the milk protein fractions (Calamari and Mariani, 1998). Further research is required to clarify the involvement of the GGT and its relationships with milk protein yield, the casein composition, and consequent milk cheesemaking properties.

Conclusion

The GGT activity in cow’s milk varies during lactation and is highest in colostrum compared with mature milk, in which GGT activity is markedly affected by lactation phase. Our results have shown that the cows categorized in a group with high or low GGT activity in milk, according to their average value of GGT activity in milk during lactation, were always categorized in the same group in consecutive lactations that were monitored. These results, performed after selection of animals with optimal mammary health status, indicate an individual effect on GGT activity in milk.

From the observed positive relationship between GGT activity and milk protein concentration and the negative relationship between GGT activity in milk with urea in plasma, it could be speculated that, in the future, the manipulation of GGT production could represent an important tool in determining the efficiency of AA utilization and milk protein concentration and its composition, especially in conditions where milk is mainly used for cheese production.

 

References

Footnotes


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