DOI: 10.1111/jpn.12259

ORIGINAL ARTICLE

Glucose transport and milk secretion during manipulated plasma insulin and glucose concentrations and during LPS-induced mastitis in dairy cows J. J. Gross, H. A. van Dorland, O. Wellnitz and R. M. Bruckmaier Veterinary Physiology, Vetsuisse Faculty, University of Bern, Bern, Switzerland

Summary In dairy cows, glucose is essential as energy source and substrate for milk constituents. The objective of this study was to investigate effects of long-term manipulated glucose and insulin concentrations in combination with a LPS-induced mastitis on mRNA abundance of glucose transporters and factors involved in milk composition. Focusing on direct effects of insulin and glucose without influence of periparturient endocrine adaptations, 18 dairy cows (28  6 weeks of lactation) were randomly assigned to one of three infusion treatments for 56 h (six animals each). Treatments included a hyperinsulinemic hypoglycaemic clamp (HypoG), a hyperinsulinemic euglycaemic clamp (EuG) and a control group (NaCl). After 48 h of infusions, an intramammary challenge with LPS from E. coli was performed and infusions continued for additional 8 h. Mammary gland biopsies were taken before, at 48 (before LPS challenge) and at 56 h (after LPS challenge) of infusion, and mRNA abundance of genes involved in mammary gland metabolism was measured by RT-qPCR. During the 48 h of infusions, mRNA abundance of glucose transporters GLUT1, 3, 4, 8, 12, SGLT1, 2) was not affected in HypoG, while they were downregulated in EuG. The mRNA abundance of alpha-lactalbumin, insulin-induced gene 1, j-casein and acetyl-CoA carboxylase was downregulated in HypoG, but not affected in EuG. Contrary during the intramammary LPS challenge, most of the glucose transporters were downregulated in NaCl and HypoG, but not in EuG. The mRNA abundance of glucose transporters in the mammary gland seems not to be affected by a shortage of glucose, while enzymes and milk constituents directly depending on glucose as a substrate are immediately downregulated. During LPS-induced mastitis in combination with hypoglycaemia, mammary gland metabolism was more aligned to save glucose for the immune system compared to a situation without limited glucose availability during EuG. Keywords glucose transporter, mammary gland metabolism, clamp, dairy cow Correspondence R. M. Bruckmaier, Veterinary Physiology, Vetsuisse Faculty, University of Bern, Bremgartenstrasse 109a, CH-3012 Bern, Switzerland. Tel: +41-31-6312324; Fax: +41-31-6312640; E-mail: [email protected] Received: 1 July 2014; accepted: 1 September 2014

Introduction In lactating dairy cows, a major portion of blood glucose (up to 85% of the total glucose entering the blood; Bickerstaffe et al., 1974; Chaiyabutr et al., 1980) is taken up by the mammary gland and predominantly used for the synthesis of milk lactose, thus also determining milk volume by maintaining its osmolarity via the uptake of water. For mammalian species, glucose is furthermore an essential substrate to provide ATP and NADPH as an energy source, involved in amino acid synthesis, and precursors for protein and lipid synthesis in mammary epithelial cells (MEC), while acetate and b-hydroxybutyrate are used

for milk fat synthesis and additional energy source in the mammary gland of ruminants. Considering the importance of glucose in lactating ruminants, the mechanisms underlying the regulation of glucose uptake into the mammary gland and subsequent utilization are subject of this research. The effects of manipulated glucose concentrations on mammary glucose transporters were mostly investigated in vitro (Zhao et al., 1999; Xiao and Cant, 2005), while in vivo studies focused on changes in gene expressions of glucose transporters during the lactation–gestation cycle in lactating dairy cows (Zhao and Keating, 2007a,b; Mattmiller et al., 2011). Altered plasma glucose concentrations do not only affect

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glucose transporters in the mammary gland, but have also an impact on genes involved in the synthesis of milk constituents (Liu et al., 2013). The hyperinsulinemic euglycaemic clamp technique is an established method to study the effects of an increased glucose turnover in dairy cows (e.g. McGuire et al., 1995; Blum et al., 1999). Several studies investigated the direct effects of short-term and long-term insulin administration on liver metabolism (Hayirli et al., 2002; Kreipe et al., 2011). In addition, changes of factors related to the immune response were modified by insulin and glucose during LPS-induced mastitis (Vernay et al., 2012). Therefore, interactions between a stimulated mammary immune system and mammary gland metabolism, and especially glucose uptake into the mammary gland during mastitis, are of particular interest. The objective of this study was to investigate the effects of long-term manipulated glucose and insulin concentrations in combination with a subsequent LPS-induced mastitis on the mRNA abundance of glucose transporters and different factors involved in milk composition in dairy cows. To avoid the confounding effects of numerous endocrine changes around parturition on the mammary gland metabolism, midlactating dairy cows were selected for this study. Materials and methods Animals and treatments

The experiment was carried out with 18 mid-lactating (16 Holstein and 2 Red Holstein 9 Simmental) dairy cows (parity: 2.9  1.3, 28  6 weeks post-partum; mean  SD). All experimental procedures followed the Swiss Federal Law on Animal Protection and were approved by the Committee of Animal Experiments of the Canton Fribourg, Switzerland. Cows were randomly assigned to one of three groups, as described in detail by Kreipe et al. (2011). Feeding and housing conditions were also described previously (Kreipe et al., 2011; Vernay et al., 2012). At the day before experimental treatment started, both jugular veins of the cows were fitted with indwelling catheters. Treatment groups (six animals each) included either a hyperinsulinemic hypoglycaemic clamp (HypoG), a hyperinsulinemic euglycaemic clamp (EuG), or an infusion with physiological saline solution for the control group (NaCl).

et al. (2011). In short, infusions were provided through one intravenous jugular catheter of one site, while blood samples for later analyses and for immediate adjustment of infusion rates were taken from the opposite catheter. In the HypoG group, the plasma glucose concentration was decreased within the first 30 min by infusion of 4 mU/kg/min insulin solution to a glucose target concentration of 2.5 mmol/L and thereafter maintained by a mean insulin infusion rate of 0.62 mU/kg/min. In the EuG group, the plasma glucose concentration was initially decreased to 3.0 mmol/L by applying 5 ml boli of 4 mU/kg insulin once every 5 min for the approximately first 30 min. Thereafter, insulin was constantly infused with a 1 mU/kg insulin solution at 0.62 mU/kg/min. After lowering the blood glucose level by insulin, its concentration was elevated again by infusion of glucose in parallel to insulin to the basal glucose concentrations before the experiment. For the NaCl group, a 0.9% saline solution was infused at a rate of 20 ml/h. Experiment 2 (LPS-induced mastitis during continued infusions from 48 to 56 h)

In experiment 2, infusions of experiment 1 were continued without interruption for additional 8 h until 56 h of infusion. At 48 h of infusion, an intramammary LPS challenge was performed as described by Vernay et al. (2012). In short, 200 lg LPS from Escherichia coli serotype O26:B6 (# L8274; SigmaAldrich, Saint Louis, MO, USA), diluted in 10 ml of NaCl (0.9%) solution, was intramammary instilled in one front and one rear quarter, while the second front and rear quarters served as control quarters (10 ml of 0.9% NaCl only). Mammary gland biopsy sampling

Infusions in all groups started at 0900 h and were performed continuously for 48 h as described by Kreipe

Mammary gland biopsies (30–60 mg) of the two rear quarters (1 LPS-challenged, 1 control) were taken 1 week before the start of the clamp infusions (0 h) and after 48 h of infusion (end of experiment 1, before experiment 2/LPS challenge). After 8 h of LPS challenge (after 56 h of continuous infusions), a third biopsy was taken. The procedure of taking mammary gland biopsies was described in more detail earlier (Schmitz et al., 2004; Kreipe et al., 2011; Vernay et al., 2012). According to the manufacturer’s instructions, biopsy samples were transferred into a RNA stabilization reagent (RNAlater, Ambion; Applied Biosystems, Austin, TX, USA), kept

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at 4 °C for 24 h and finally stored at 80 °C until RNA extraction.

were considered to be significant if p < 0.05 or as a trend if (0.05 ≤ p < 0.10).

mRNA extraction and RT-qPCR

Results

Total RNA was extracted from the mammary gland biopsies with peqGOLD TriFastTM (PEQLAB Biotechnologie GmbH, Erlangen, Germany) according to the manufacturer’s protocol. Final RNA concentration and quality was measured by spectrophotometry (NanoDrop 2000; Thermo Fischer Scientifics Inc., Waltham, MA, USA). Details on the reverse transcription and subsequent PCR analysis were described in more detail by Wellnitz et al. (2011) and Vernay et al. (2012). Target genes [glucose transporter (GLUT) 1, GLUT3, GLUT4, GLUT8, GLUT12, sodium-dependent glucose transporter (SGLT) 1, SGLT2, kinase insert domain receptor (KDR), hypoxia-inducible factor (HIF) 1a, insulin-induced gene (INSIG) 1, insulin receptor (INSR), alpha-lactalbumin (ALA), UDPglucose pyrophosphorylase (UGP) 2, kappa-casein (j-CN), alphaS1-casein (aS1-CN), fatty acid synthase (FASN), sterol regulatory element-binding factor (SREBF) 1, acetyl-CoA carboxylase (ACC)] were normalized to the abundance of three housekeeping genes (GAPDH, ubiquitin and cyclophilin B). Primer details of target and housekeeping genes are given in Table 1. To show infusion-related changes on parameters of the mammary gland metabolism, the average of the mRNA expression of both biopsied quarters of each target gene and animal was calculated at 0 h and after 48 h of infusion (before LPS challenge). Changes of mammary mRNA expression induced by the LPS challenge were shown in the LPS and control quarter separately as difference between the expression level after 56 h of infusion (8 h after LPS application) and 48 h of infusion (before LPS challenge).

Experiment 1 (Infusion up to 48 h)

Statistical analysis

Data are presented as means  SEM. The changes (differences between before and 48 h after the start of infusions, and before and after LPS administration) were calculated for mRNA abundance of target genes. These changes of mRNA abundance of measured genes were analysed using the general linear models (GLM) procedure of SAS (version 9.2; SAS Institute Inc., Cary, NC, USA), including treatment (HypoG, EuG or NaCl) as fixed effect. Differences between means were localized by Tukey’s test. In addition, means of delta values obtained within each treatment were tested for their difference from ‘0’. Differences Journal of Animal Physiology and Animal Nutrition © 2014 Blackwell Verlag GmbH

Data on the changes of mRNA abundances during 48 h of infusions are shown in Table 2. In HypoG, mRNA abundance of glucose transporters [GLUT1, GLUT3, GLUT4, GLUT8, GLUT12, sodium-dependent glucose transporter (SGLT) 1, SGLT2] and aS1-casein (CN), fatty acid synthase (FASN) and sterol regulatory element-binding factor 1 (SREBF1) did not respond to long-term insulin infusion and the subsequent associated reduced plasma glucose concentration (p > 0.05). Expression of GLUT1 was downregulated in HypoG compared to NaCl (p < 0.05, Table 2), whereas mRNA abundance of GLUT4 was lower in EuG compared to HypoG (p < 0.05, Table 2). The mRNA abundance of kinase insert domain receptor (KDR) and hypoxiainducible factor 1a (HIF1a) was not affected by treatment (p > 0.05). In EuG, however, most of the glucose transporters were downregulated (GLUT4 and GLUT12, p < 0.05; SGLT1 and SGLT2, p < 0.10), while mRNA abundance of others (GLUT1, GLUT3, GLUT8) did not respond to treatment either. While insulin-induced gene 1 (INSIG1) tended to be downregulated in HypoG, its expression was upregulated in EuG (p < 0.05). Expression of INSIG1 was upregulated in EuG compared to NaCl and HypoG (p < 0.05, Table 2). The mRNA abundance of insulin receptor (INSR), aS1-CN, FASN and SREBF1 was not affected in HypoG cows, but in EuG. On the other hand, ALA, UDP-glucose pyrophosphorylase 2 (UGP2), j-CN and acetyl-CoA carboxylase (ACC) mRNA abundances did not change after 48 h of infusions in EuG, but in HypoG. The mRNA abundance of j-CN and aS1-CN was different between HypoG and EuG (p < 0.05). Experiment 2 (LPS-induced mastitis during continued infusions from 48 to 56 h)

The intramammary LPS challenge resulted in changes of mRNA abundances of most studied parameters in the LPS and control quarter of the NaCl group (Table 3). Glucose transporters (except GLUT3) and factors involved in hypoxia, milk protein and lipid metabolism (except HIF1a) were downregulated (p < 0.05), whereas INSIG1, UGP2 and aS1-CN showed no response (p > 0.05, Table 3). Expressions of GLUT3 and GLUT4 were different among HypoG and EuG in the LPS stimulated quarter (p < 0.05, Table 3), but not in the control quarter. 749

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Table 1 PCR primer information, the annealing temperature and the PCR product length for the genes analysed in mammary gland samples Gene Target genes GLUT1

for rev GLUT3 for rev GLUT4 for rev GLUT8 for rev GLUT12 for rev SGLT1 for rev SGLT2 for rev KDR for rev HIF1a for rev INSIG1 for rev INSR for rev ALA for rev UGP2 for rev j-CN for rev aS1-CN for rev FASN for rev SREBF1 for rev ACC for rev Housekeeping genes GAPDH for rev Ubiquitin for rev Cyclophilin B for rev

Sequence 50 –30

GenBank accession no.

Annealing temperature (°C)

Product length

GCT TCT CCA ACT GGA CTT CG ACA GCT CCT CAG GTG TCT TG GGA AAA CTT GCC GCC GAT AG CGC CTC AGG AGC ATT GAT GA GAC TGG TAC CCA TGT ACG TG CCG GAT GAT GTA GAG GTA GC AGT GAC TGC CCG TCC TTG CT TGC TGT CCT GGC TCC TGA CT CCT GGC ATC CTT ACC AAA TG GCA GCA ACG TAA ACA AGC AA AGC GTA TTG ACC TGG ATG CA TCC GAG GTG TCT GTC ATC TT TAC CCA GGA GGA GAC GAC TG CAG GGT GTG GCT ATG GAC TG GCC AAT GGA GGG GAA CTG AA GTG TTC ACC GTG TGT TGC TC CCA CGA GGA AAT GAG AGA AAT GCTT CCG CTG TGT ATT TTG CTC TTT ACC CAC GTC AGT GCT AAA CTG GA GAT AGA CTC CGT TGT ACA CC TCC TCA AGG AGC TGG AGG AGT GCT GCT GTC ACA TTC CCC A CTC TGC TCC TGG TAG GCA TC ACA GAC CCA TTC AGG CAA AC CAA CCT ATG GAT CTC TCT TG GTA GGA AAT TCC CGC TTT TC ACC AAC AGA AAC CAG TTG CAC CTA CAG TGC TCT CTA CTG CTT GAA CTG AGC AAG GAT ATT GGG A TAG GCA TCC AGC TGG TAG AAT CTG AGT CGG AGA ACC TGG AG ACA ATG GCC TCG TAG GTG AC CCA GCT GAC AGC TCC ATT GA TGC GCG CCA CAA GGA CTC TTC CGA CAG GTT CAA GC ACC ATC CTG GCA AGT TTC AC

NM_174602

60

225

NM_174603

60

223

NM_174604.1

60

242

NM_201528.1

61

133

NM_001011683.1

60

123

NM_174606.2

60

205

NM_203360.1

60

297

XM_611785

60

264

NM_174339

61

76

NM_001077909

60

178

XM_005208817

62

127

BT_025469

60

125

NM_174212

60

288

M36641

62

303

M33123

60

362

NM_001012669

63

232

NM_001113302

53

67

AJ_132890

61

248

NM_001034034

60

197

NM_174133

62

198

NM_174152

60

174

GTC TTC ACT ACC ATG GAG AAG G TCA TGG ATG ACC TTG GCC AG AGA TCC AGG ATA AGG AAG GCA T GCT CCA CCT CCA GGG TGA T GGT CAT CGG TCT CTT TGG AA GAT GCT CTT ACC TCC AGT GC

GLUT, glucose transporter; SGLT, sodium-dependent glucose transporter; KDR, kinase insert domain receptor; HIF1a, hypoxia-inducible factor 1a; INSIG1, insulin-induced gene 1; INSR, insulin receptor; ALA, alpha-lactalbumin; UGP2, UDP-glucose pyrophosphorylase 2; j-CN, kappa-casein; aS1-CN, alphaS1-casein; FASN, fatty acid synthase; SREBF1, sterol regulatory element-binding factor 1; ACC, acetyl-CoA carboxylase; GAPDH, glyceraldehydes 3-phosphate dehydrogenase.

Contrary to the LPS stimulated quarter in NaCl, mRNA abundance of GLUT1, GLUT12, SGLT2, KDR, j-CN and SREBF1 was not changed by LPS application in HypoG (Table 3). However, expression of GLUT12, SGLT2 and KDR were different among NaCl and EuG (p < 0.05, Table 3).

In EuG and contrary to NaCl and HypoG, the LPS-challenged mammary quarter did not show differences in the expression of glucose transporters with the exception of GLUT4 that was upregulated (p < 0.05, Table 3). While the mRNA abundance of INSIG1 was not affected by group and LPS treatment,

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Table 2 Changes of mRNA abundance of genes related to mammary gland metabolism during 48 h infusion with insulin + glucose (EuG), insulin (HypoG) or saline (NaCl). Delta values (differences between before and 48 h after the start of infusions) represent mean  SEM Delta (48 h–0) Parameter

NaCl

GLUT1 GLUT3 GLUT4 GLUT8 GLUT12 SGLT1 SGLT2 KDR HIF1a INSIG1 INSR ALA UGP2 jCN aS1CN FASN SREBF1 ACC

0.33 0.14 0.43 0.45 0.23 0.29 0.45 0.38 0.47 0.31 0.10 0.17 0.26 0.62 0.39 0.18 0.13 0.04

                 

0.21 0.30 0.47 0.35 0.27 0.39 0.39 0.43 0.27 0.47 0.20 0.64 0.46 0.66 0.20+ 0.39 0.36 0.43

ANOVA

(p-value, group)

HypoG

EuG

NaCl 9 HypoG

0.21  0.14 0.15  0.37 0.43  0.31 0.03  0.30 0.10  0.24 0.06  0.36 0.01  0.18 0.31  0.27 0.16  0.37 0.43  0.20+ 0.11  0.21 0.86  0.23* 1.48  0.52* 1.26  0.29* 0.23  0.23 0.31  0.22 0.15  0.16 1.00  0.26*

0.24  0.15 0.54  0.49 0.78  0.26* 0.21  0.19 0.99  0.40* 0.49  0.26+ 0.47  0.22+ 0.13  0.34 0.24  0.32 0.69  0.18* 0.52  0.22* 0.12  0.31 0.14  0.45 0.24  0.36 0.48  0.21* 0.53  0.24* 0.40  0.16* 0.02  0.35

p p p p p p p p p p p p p p p p p p

< = = = = = = = = = = = = = = = = =

0.05 0.60 0.11 0.26 0.77 0.65 0.26 0.91 0.19 0.80 0.98 0.11 0.09 0.34 0.60 0.25 0.43 0.05

NaCl 9 EuG p p p p p p p p p p p p p p p p p p

= = = = = = = = = < = = = = < = = =

0.71 0.49 0.51 0.56 0.10 0.67 0.97 0.62 0.62 0.05 0.05 0.64 0.57 0.21 0.05 0.41 0.44 0.91

HypoG 9 EuG p p p p p P p p p p p p p p p p p p

= = < = = = = = = < = = < < < = = =

0.08 0.24 0.05 0.57 0.06 0.38 0.24 0.71 0.40 0.05 0.05 0.24 0.05 0.05 0.05 0.06 0.13 0.07

GLUT, glucose transporter; SGLT, sodium-dependent glucose transporter; KDR, kinase insert domain receptor; HIF1a, hypoxia-inducible factor 1a; INSIG1, insulin-induced gene 1; INSR, insulin receptor; ALA, alpha-lactalbumin; UGP2, UDP-glucose pyrophosphorylase 2; j-CN, kappa-casein; aS1-CN, alphaS1-casein; FASN, fatty acid synthase; SREBF1, sterol regulatory element-binding factor 1; ACC, acetyl-CoA carboxylase. From 0 different delta values are in bold type and marked with *p < 0.05 or + p < 0.10.

INSR was downregulated in the LPS quarter of NaCl and HypoG, but not in EuG. Expression of INSR was different among NaCl and EuG, as well as among HypoG and EuG in both LPS stimulated and control quarter (p < 0.05, Table 3).

With the present study, we investigated the effects of long-term manipulated glucose and insulin concentrations in combination with a subsequent LPS-induced mastitis on mRNA abundance of glucose transporters and different factors involved in milk composition in dairy cows. A major role in enabling glucose uptake is hold by the facilitative glucose transporters (Zhao and Keating, 2007a,b). The insulin-independent GLUT1 is considered to be responsible for the basal glucose uptake into the bovine mammary gland (Zhao and Keating, 2007a,b). In the present study, GLUT1 expression was not affected by lowered or elevated glucose availability during the first 48 h of infusions. This emphasizes the involvement of GLUT1 in ensuring basal glucose supply of the mammary gland. Other tissues and cells may react differently to a manipulation of glucose and insulin concentration, for example

in bovine chromaffin cells, mRNA abundance of GLUT1 was reported to be upregulated by glucose deprivation (Zhao and Keating, 2007a,b). Besides metabolic processes, glucose is also needed for the immune system. During the LPS-induced mastitis in the present study, only the LPS-treated quarter in the control group showed a downregulation of GLUT1. This effect is due to the insulin resistance present during the LPS stimulation that reduced glucose concentration only in the control group but not in HypoG and EuG (Vernay et al., 2012). Mainly present in brain and neuronal cells (Zhao and Keating, 2007a,b), GLUT3 expression was also confirmed for the mammary gland (Mattmiller et al., 2011). In the present study, GLUT3 was not affected by changed glucose and insulin concentrations and confirms previous findings to be a non-insulinsensitive member of the GLUT family (Wood and Trayhurn, 2003). During the LPS challenge in the present study, when glucose is an energy substrate for the local and systemic immune response, GLUT3 expression was found to be upregulated except in EuG, where glucose concentration in plasma was maintained by infusion. Unlike GLUT1 and GLUT3, GLUT4 is known as the major insulin-responsive glucose transporter. Under

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Discussion

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1.20  0.40* 1.30  0.32* 1.82  0.22* 2.09  0.39* 2.90  0.64* 1.90  0.72* 1.57  0.45* 2.31  0.37* 0.88  0.34* 0.78  0.43 2.00  0.55* 5.29  1.55* 0.29  0.79 1.96  0.80+ 0.76  0.66 4.79  0.91* 1.36  0.55+ 1.77  0.51*

0.15  0.35 1.53  0.58* 0.79  0.73 0.16  0.51 0.08  0.53 0.08  0.81 0.67  0.44 0.05  0.52 1.73  0.40* 0.02  0.44 1.38  0.16* 2.80  0.74* 1.19  0.96 0.22  0.47 0.91  0.31* 1.19  0.38* 0.34  0.41 1.36  0.41*

GLUT1 GLUT3 GLUT4 GLUT8 GLUT12 SGLT1 SGLT2 KDR HIF1a INSIG1 INSR ALA UGP2 jCN aS1CN FASN SREBF1 ACC

0.42  0.53 1.18  0.22* 0.43  0.37 0.43  0.67 0.34  0.37 0.92  1.00 0.42  0.26 0.68  0.81 0.47  0.50 0.65  0.42 1.24  0.73 3.40  2.19 0.92  1.06 1.67  1.97 1.43  0.29* 1.11  0.54 0.06  0.48 0.29  0.57

Delta Con qu

HypoG

0.06  0.51 2.47  0.29* 0.75  0.30+ 1.30  0.49+ 0.75  0.63 1.59  0.56* 0.56  0.31 1.07  0.55 0.99  0.41+ 0.58  0.40 1.16  0.39* 2.84  1.00* 2.43  1.26 1.91  1.04 0.87  0.21* 4.32  0.72* 0.90  0.54 2.35  0.67*

Delta LPS qu 0.53  0.29 2.38  0.37* 0.32  0.70 0.24  0.57 0.63  0.51 1.16  0.59 0.18  0.37 0.49  0.41 2.43  0.48* 0.09  0.18 0.15  0.41 0.39  0.52 0.17  0.61 0.70  0.55 0.14  0.24 0.99  0.44+ 2.47  2.93 0.46  0.28

Delta Con qu

EuG

0.42  0.22 0.67  1.11 0.91  0.18* 0.83  0.49 0.87  0.92 0.08  0.72 0.31  0.27 0.62  0.54 0.35  0.63 0.01  0.31 0.24  0.22 2.14  0.25* 0.26  0.47 0.77  0.24* 1.04  0.43+ 3.19  0.83* 0.95  0.18* 1.10  0.49+

Delta LPS qu

control

p p p p p p p p p p p p p p p p p p

= = = = = = < = = = = = = = = = = = 0.62 0.69 0.09 0.44 0.78 0.36 0.05 0.35 0.08 0.22 0.82 0.73 0.10 0.29 0.38 0.94 0.88 0.14

p p p p p p p p p p p p p p p p p p

= = = = = = = = = = < = = = = = = = 0.21 0.31 0.49 0.59 0.42 0.30 0.33 0.55 0.29 0.96 0.05 0.68 0.26 0.71 0.07 0.84 0.14 0.20

p p p p p p p p p p p p p p p p p p

= = = = = = = = < = < = = = < = = =

0.09 0.17 0.14 0.79 0.30 0.06 0.27 0.14 0.05 0.18 0.05 0.08 0.55 0.48 0.05 0.90 0.20 0.81

p p p p p p p p p p p p p p p p p p

< = = = < = = = = = = = < = = = = =

0.05 0.19 0.14 0.30 0.05 0.78 0.07 0.12 0.87 0.72 0.19 0.16 0.05 0.97 0.68 0.64 0.81 0.42

NaCl 9 HypoG

NaCl 9 HypoG

p p p p p p p p p p p p p p p p p p

= = < = < = < < = = < = = = < = = =

0.15 0.45 0.05 0.09 0.05 0.08 0.05 0.05 0.42 0.14 0.05 0.06 0.65 0.36 0.05 0.10 0.82 0.33

NaCl 9 EuG

p p p p p p p p p p p p p p p p p p

= < < = = = = = = = < = < = < = = =

0.52 0.05 0.05 0.53 0.90 0.17 0.63 0.56 0.36 0.29 0.05 0.68 0.05 0.40 0.05 0.25 0.98 0.09

HypoG 9 EuG

(p-value, group) LPS quarter ANOVA

HypoG 9 EuG

group)

NaCl 9 EuG

(p-value,

quarter

ANOVA

GLUT, glucose transporter; SGLT, sodium-dependent glucose transporter; KDR, kinase insert domain receptor; HIF1a, hypoxia-inducible factor 1a; INSIG1, insulin-induced gene 1; INSR, insulin receptor; ALA, alpha-lactalbumin; UGP2, UDP-glucose pyrophosphorylase 2; j-CN, kappa-casein; aS1-CN, alphaS1-casein; FASN, fatty acid synthase; SREBF1, sterol regulatory element-binding factor 1; ACC, acetyl-CoA carboxylase. From 0 different delta values are in bold type and marked with *p < 0.05 or + p < 0.10.

Delta LPS qu

Delta Con qu

Parameter

NaCl

Table 3 Changes of mRNA abundance of genes related to mammary gland metabolism during the LPS challenge in LPS and control quarters in dairy cows infused with insulin + glucose (EuG), insulin (HypoG) or saline (NaCl). Delta values (differences between before and after the LPS challenge) represent mean  SEM

Glucose effects on mammary metabolism J. J. Gross et al.

Journal of Animal Physiology and Animal Nutrition © 2014 Blackwell Verlag GmbH

J. J. Gross et al.

Glucose effects on mammary metabolism

insulin stimulation, translocation of GLUT4 to the cell surface results in an increased glucose transport activity (Zhao and Keating, 2007a,b). In the present study, an increased insulin concentration alone did not affect the mRNA abundance of GLUT4, while a simultaneous glucose infusion decreased GLUT4 expression. Mattmiller et al. (2011) found that with advancing lactation, GLUT4 gains in its importance in mammary glucose transport, when the lactating mammary gland is more integrated in the homoeostatic control and is more sensitive to insulin regulation. In turn, GLUT4 decreases when enough glucose is available as during the hyperinsulinemic euglycaemic clamp in the present study. Interestingly, GLUT4 expression is decreased during the intramammary LPS challenge except when glucose availability was maintained as observed for the EuG group. GLUT8 mRNA levels increase dramatically during late pregnancy to early lactation in bovine mammary gland, indicating a potential role in glucose uptake for milk synthesis in this tissue (Zhao and Keating, 2007a, b). The regulation of GLUT8 is poorly understood (Zhao et al., 2004). Except for the response of GLUT8 expression to oestrogen in male testes, hormonal regulation of GLUT8 is unclear. Insulin was shown to stimulate GLUT8 translocation in blastocysts, but not in fat cells and neuroblasts (Zhao et al., 2004). While GLUT8 expression was not affected by manipulated glucose and insulin concentrations in the present study, it was decreased during the intramammary LPS challenge except the EuG group. Zhao et al. (2004) suppose that there is some evidence indicating that glucose itself may influence the expression of GLUT8, but up to now it is not clear whether glucose itself or insulin affect GLUT8 expression. GLUT12 is an insulin-responsive glucose transporter that is also expressed in the bovine mammary gland (Zhao and Keating, 2007a,b). Miller et al. (2005) reported that GLUT12 may be another insulinsensitive GLUT in humans, but not in the bovine mammary gland. In the present study, however, expression of GLUT12 was similarly affected as GLUT4 in the EuG treatment indicating that both are insulinsensitive. The expression of SGLT1 as a high-affinity glucose transporter has been observed in the mammary gland (Zhao and Keating, 2007a,b). SGLT2 is known to be a low-affinity glucose transporter, but its role in the mammary gland is unclear (Zhao and Keating, 2007a, b). The physiological roles of these SGLTs in the mammary gland remain to be studied (Zhao, 2013). Both SGLT1 and SGLT2 mRNA abundances tended to be decreased during the hyperinsulinemic euglycaemic

clamp in the present study. Compared to the other findings regarding regulation of glucose transporters in the present study, an insulin-responsive mechanism affecting SGLT1 and SGLT2 might not be excluded. Besides glucose uptake into the MEC, glucose is released from the cytoplasm to the milk across the apical membrane by GLUT8, GLUT12 and SGLT1 in cows (Zhao, 2013). The decreased expressions of GLUT8, GLUT12 and SGLT1 during the LPS challenge might be a mechanism to save glucose during inflammatory processes. Mattmiller et al. (2011) confirmed that increased metabolic activities in the mammary gland during the transition period result in hypoxia, which can stimulate GLUT1 expression in bovine endothelial cells (Loike et al., 1992). Hypoxia-inducible factor 1a (HIF1a) is responsible for the upregulation of angiogenic factors such as vascular endothelial growth factor (VEGF) during hypoxic conditions (Mattmiller et al., 2011). Hypoxia is generally considered a side effect of inflammation (Nizet and Johnson, 2009). Angiogenesis induced by VEGF, which binds to cellsurface receptors known as kinase insert domain receptor (KDR) that mediate VEGF responses, increases oxygen availability in the endothelium and thus alleviates hypoxia (Mattmiller et al., 2011). Expression of KDR and HIF1a was not affected by different infusions in the present study, indicating that hypoxia status was not affected by manipulated glucose and insulin concentrations in mid- and late-lactating dairy cows used here. During the LPS challenge, HIF1a seemed to be upregulated in the untreated and LPS quarters, but not in the EuG group. This suggests a possible role of glucose availability on the response to hypoxia during inflammatory processes. In agreement with our findings, Moyes et al. (2009) observed an upregulation of HIF1a after an intramammary infection (IMI) with S. uberis. Hypoxia allows the diversion of metabolic resources normally used to synthesize milk to support the immune system (Silanikove et al., 2011). The quarters with an increased HIF1a expression indicating hypoxia during the LPS challenge in the present study also showed an increase in GLUT3 expression, but not in GLUT1. Similar responses of GLUT1 and GLUT3 due to HIF1a activation were shown by Shao and Zhao (2014), who concluded that glucose transport is stimulated by hypoxia. While in the present study GLUT1 expression was not affected by hypoxia during the LPS challenge, GLUT8 was downregulated in agreement with the findings of Shao and Zhao (2014).

Journal of Animal Physiology and Animal Nutrition © 2014 Blackwell Verlag GmbH

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Glucose effects on mammary metabolism

J. J. Gross et al.

Glucose is an important substrate to synthesize milk fat, protein and lactose. Genes encoding for acetylCoA carboxylase (ACC) and fatty acid synthase (FASN) are known to be involved in key processes of lipogenesis within the mammary gland. The downregulation of ACC in the present study during hypoglycaemia supports the findings of Kreipe et al. (2011), who reported a reduced milk yield due to less glucose available for lactose production. However, fat yield in cows experiencing hypoglycaemia was unaffected (Kreipe et al., 2011). When glucose turnover was higher as for the EuG group, FASN was upregulated and milk fat content and yield maintained (see Kreipe et al., 2011) despite the simultaneous high glucose clearance by insulin infusion. Liu et al. (2013) found that high concentrations of glucose did not affect the mRNA abundance of ACC, while FASN was expressed at a lower level. The sterol regulatory element-binding factor 1 (SREBF1) plays an important role in activating genes involved in milk fat synthesis (Edwards et al., 2000; Bauman et al., 2008). During the hyperinsulinemic euglycaemic clamp in the present study, INSIG1 mRNA abundance was elevated. INSIG1 is involved in the inhibition of SREBF inactivation and is thus in the broader sense integrated in the lipid metabolism of the mammary gland (Moyes et al., 2009). During the LPS challenge in the present study, expression of INSIG1 was not affected, whereas by an IMI with S. uberis INSIG1 was upregulated (Moyes et al., 2009). It needs to be determined, if mammary gland metabolism shows pathogen specific differences during inflammations. In the present study, an upregulation of SREBF1 was followed by an upregulation of FASN in the EuG group. In the study of Liu et al. (2013), SREBF1 mRNA abundance in BMEC was elevated at an intermediate glucose concentration, while at lower or higher concentrations its expression was decreased. In the present study, hypoglycaemia in combination with a LPS-induced mastitis led to a reduced expression of SREBF1, FASN and ACC. This along with the simultaneous insulin resistance might spare glucose for the immune system (Vernay et al., 2012). Confirming our results, Moyes et al. (2009) showed that an IMI with S. uberis resulted in a downregulation of genes associated with milk fat synthesis. Liu et al. (2013) also considered the simultaneous regulation of lipogenic genes in other tissues (e.g. adipose tissue) besides the mammary gland. This effect needs to be kept in mind among direct responses of mammary gland metabolism and milk composition.

The essential role of glucose for lactose synthesis in mammals is commonly indisputable. During hypoglycaemia before and after the LPS challenge, expression of ALA (subunit of lactose synthase) was clearly downregulated in the present study and confirmed by a lowered lactose content in milk (see Kreipe et al., 2011). No obvious changes of ALA expression were detected in BMEC exposed to various levels of glucose (Liu et al., 2013). A common feature of clinical and subclinical mastitis is the reduction in milk lactose content (Lindmark-Mansson et al., 2006). The reduction in lactose content is rather due to a reduced lactose synthesis than its loss due to leakage into the blood by disrupted tight junctions (Leitner et al., 2011). Confirming our findings, Moyes et al. (2009) report a downregulation of ALA during an IMI with S. uberis. A decrease in lactose synthesis reduces substrate (i.e. lactose) supporting the growth of bacteria and potentially preventing the inhibition of PMN phagocytosis by lactose (Moyes et al., 2009). Ollier et al. (2007) found in feed-deprived lactating goats a downregulation in the expression of milk proteins such as ALA and aS1-CN when plasma insulin and glucose concentrations were lowered at the same time. The mRNA abundance of aS1-CN in the present study was downregulated when simultaneously high levels of insulin and glucose were present. Besides effects on glucose metabolism, amino acid availability is affected by insulin as well (Bequette et al., 2001). Therefore, gene expressions related to milk protein synthesis may not only be affected by glucose alone. A hypoglycaemic condition during the intramammary LPS challenge decreased expression of aS1-CN in the control quarters for NaCl and HypoG group and also for the infected quarter in HypoG. Kappa-CN tended to be downregulated only in the LPS quarter of the control group. Vanselow et al. (2006) showed that mastitis caused by E. coli abolishes casein synthesis in the infected quarter, but not in the uninfected control quarter of the same animals. In the present study, mammary gland biopsies were taken after 8 h of the LPS challenge. Unfortunately, milk composition was not followed further. Vanselow et al. (2006) showed that the average casein content remains constant during the first 12 h post-infection. However, then it drops sharply down to

Glucose transport and milk secretion during manipulated plasma insulin and glucose concentrations and during LPS-induced mastitis in dairy cows.

In dairy cows, glucose is essential as energy source and substrate for milk constituents. The objective of this study was to investigate effects of lo...
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