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Feeding level regulates the expression of some genes involved with programed cell death and remodeling in goat and sheep mammary tissue

Published online by Cambridge University Press:  13 November 2020

Eleni Tsiplakou*
Affiliation:
Department of Animal Science, School of Animal Biosciences, Agricultural University of Athens, Iera Odos 75, GR-11855, Athens, Greece
Christina Mitsiopoulou
Affiliation:
Department of Animal Science, School of Animal Biosciences, Agricultural University of Athens, Iera Odos 75, GR-11855, Athens, Greece
Dimitrios Skliros
Affiliation:
Laboratory of Molecular Biology, Department of Biotechnology, School of Applied Biology and Biotechnology, Agricultural University of Athens, Iera Odos 75, GR-11855, Athens, Greece
Alexandros Mavrommatis
Affiliation:
Department of Animal Science, School of Animal Biosciences, Agricultural University of Athens, Iera Odos 75, GR-11855, Athens, Greece
Emmanouil Flemetakis
Affiliation:
Laboratory of Molecular Biology, Department of Biotechnology, School of Applied Biology and Biotechnology, Agricultural University of Athens, Iera Odos 75, GR-11855, Athens, Greece
*
Author for correspondence: Eleni Tsiplakou, Email: eltsiplakou@aua.gr
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Abstract

Mammary tissue (MT) turnover is characterized by programed cell death and remodeling which might be affected by both feeding level and animal species. Thus, twenty-four dairy goats and the same number of sheep were assigned to three homogenous sub-groups per animal species and fed the same diet in quantities which met 70% (FL70), 100% (FL100) and 130% (FL130) of their daily energy and crude protein requirements. Individual MT samples were taken by biopsy from the animals on the 30th and 60th experimental day. The results showed, in the first sampling time, a significant reduction in the mRNA abundance for selected genes involved in programed cell death in both FL 70 fed goats (STAT3 and BECN1) and sheep (CASPASE8 and BECN1) compared with the respective FL100 groups. The FL130, in comparison with the FL100, caused a significant increase in transcripts accumulation of STAT3 gene in both sampling times and CASPASE8 gene in the second sampling time in goat MT, while the opposite happened for the mRNA expression of CASPASE8 and BECN1 genes in sheep MT, but only in the first sampling time. Moreover, a significant up regulation in the mRNA levels of MMP2 gene in MT of FL130 fed sheep was observed. The FL130, in comparison with the FL70, caused an enhancement in the mRNA expression levels of BECN1, CASPASE8, BAX and STAT3 genes in goat MT only. It was also shown that apoptosis and autophagy can be affected simultaneously by the feeding level. Overfeeding affects MT programed cell death and remodeling by a completely different way in goats than sheep. In conclusion, feeding level and animal species have strong effects on both MT programed cell death (apoptosis and autophagy) and remodeling but the molecular mechanisms need further investigation.

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press on behalf of Hannah Dairy Research Foundation

In addition to genetic and nutritional factors, milk production potential is shaped by the number of mammary epithelial cells and by the mammary tissue (MT) organization (Knight, Reference Knight2000; Capuco et al., Reference Capuco, Ellis, Hale, Long, Erdman, Zhao and Paape2003; Yart et al., Reference Yart, Lollivier, Finot, Dupont, Wiart, Boutinaud, Marnet and Dessauge2013). The mammary secretory tissue organization is modulated by the ratio between cell proliferation and apoptosis (programed cell death, PCD) as well as by the metalloproteinase activity, in a procedure known as mammary cell turnover (Stefanon et al., Reference Stefanon, Colitti, Gabai, Knight and Wilde2002). Although the majority of mammary cell turnover is taking place during late pregnancy and prior to lactation, cell proliferation and apoptosis have also been observed, in cows (Capuco et al., Reference Capuco, Wood, Baldwin, McLeod and Paape2001), goats (Knight and Peaker, Reference Knight and Peaker1984) and rodents (Tucker, Reference Tucker1969), during established lactation (Wall and McFadden, Reference Wall, McFadden and Chaiyabutr2012).

Numerous genes are involved in the regulation of mammary cell turnover. More specifically, the signal transducer and activator of transcription 3 (encoded by the STAT3 gene) (Chapman et al., Reference Chapman, Lourenco, Tonner, Flint, Selbert, Takeda, Akira, Clarke and Watson2000; Colitti and Farinacci, Reference Colitti and Farinacci2009; Piantoni et al., Reference Piantoni, Wang, Drackley, Hurley and Loor2010), the caspase 8 (encoded by the CASPASE8 gene) (Gajewska et al., Reference Gajewska, Gajkowska and Motyl2005) as well as the pro-apoptotic bcl-2-like protein 4 (encoded by the BAX gene) (Schorr et al., Reference Schorr, Li, Bar-Peled, Lewis, Heredia, Lewis, Knudson, Korsmeyer, Jager, Weiher and Furth1999; Walton et al., Reference Walton, Wagner, Rucker, Shillingford, Miyoshi and Hennighausen2001) are proteins critical for the initiation of apoptosis. However, lysosomal cell death has also received attention in the last years (Boya and Kroemer, Reference Boya and Kroemer2008; Aits et al., Reference Aits, Kricker, Liu, Ellegaard, Hämälistö, Tvingsholm, Corcelle-Termeau, Høgh, Farkas, Holm Jonassen, Gromova, Mortensen and Jäättelä2015) and is independent of the executioner caspases, but does require the activity of STAT3 in order to upregulate the expression of lysosomal proteases such as cathepsin B (encoded by the CTSB gene) (Kreuzaler et al., Reference Kreuzaler, Staniszewska, Li, Omidvar, Kedjouar, Turkson, Poli, Flavell, Clarkson and Watson2011). Moreover, autophagy is another type of cell death, with beclin-1 protein (encoded by the BECN1 gene) to be considered as one of its most reliable markers (Gajewska et al., Reference Gajewska, Gajkowska and Motyl2005). Finally, the matrix metalloproteinase 2 (encoded by the MMP2 gene) and 9 (encoded by the MMP9 gene) respectively, break down the extra-cellular matrix, resulting in a second wave of apoptosis and MT remodeling (Green and Lund, Reference Green and Lund2005).

Many research studies in dairy ruminants, using immunohistochemical techniques, have shown that nutrient availability, and more specifically energy restriction, reduce the number of mammary epithelial cells (Colitti et al., Reference Colitti, Stradaioli and Stefanon2005; Dessauge et al., Reference Dessauge, Lollivier, Ponchon, Bruckmaier, Finot, Wiart, Cutullic, Disenhaus, Barbey and Boutinaud2011), increase (Dessauge et al., Reference Dessauge, Lollivier, Ponchon, Bruckmaier, Finot, Wiart, Cutullic, Disenhaus, Barbey and Boutinaud2011) or do not modify apoptosis (Nørgaard et al., Reference Nørgaard, Sørensen, Sørensen, Andersen and Sejrsen2005) and inhibit mammary cell proliferation at 8 wk, but not at 16 wk postpartum (Nørgaard et al., Reference Nørgaard, Sørensen, Sørensen, Andersen and Sejrsen2005). However, to the best of our knowledge, the impact of feeding level on the molecular regulation of mammary cell turnover remains poorly documented. Up to now, only the effect of negative energy balance on the mRNA abundance of genes encoding proteins, indicative of mammary cell turnover, has been studied in cows (Dessauge et al., Reference Dessauge, Lollivier, Ponchon, Bruckmaier, Finot, Wiart, Cutullic, Disenhaus, Barbey and Boutinaud2011) and goats (Ollier et al., Reference Ollier, Robert-Granie, Bernard, Chilliard and Leroux2007). Moreover, both Boutinaud et al. (Reference Boutinaud, Ben Chedly, Delamaire and Guinard-Flament2008) and Sigl et al. (Reference Sigl, Meyer and Wiedemann2008) studied the impact of feed restriction in the expression of some genes involved in the apoptosis of bovine mammary epithelial cells purified from milk. Thus, the objective of this study was to investigate the effect of feeding level on the mRNA expression of some genes involved in programed cell death (STAT3, CASPASE8, BAX, CTSB, BECN1) and remodeling (MMP2 and MMP9) in goat and sheep mammary tissue.

Materials and methods

Experimental design

Twenty-four 3 to 4-years-old Friesian crossbred dairy sheep and twenty-four 3 to 4-years-old Alpine cross bred dairy goats were maintained at the animal house of the Agricultural University of Athens. Housing and care of the animals conformed to Ethical Committee guidelines of Faculty of Animal Science and to EU standards for the protection of animals used for scientific purposes and/or feed legislation.

Three months post-partum (90 ± 8 d in milk) both animal species were assigned into three homogenous sub-groups (n = 8) balanced by their body weight (BW) and fat corrected milk yield. The average initial BW and milk yield was 59.1 ± 4.1 and 1.01 ± 0.20 kg/d respectively for sheep, and 53.1 ± 2.1 and 0.70 ± 0.08 kg/d for goats. Each animal of both groups was fed individually throughout the experimental period which lasted 60 d. The three groups (treatments) of both animal species were fed with the same diet which covered 70% (FL70), 100% (FL100) and 130% (FL130) of their daily individual energy and crude protein requirements, respectively (National Research Council, 1981; Zervas, Reference Zervas2007). The quantities of food offered to the animals were adjusted on a group basis at 0, 12, 24, 31, 39 and 52 experimental day in order to meet the 70%, 100% and 130% of animal's requirements of each group, respectively. The diet given to both animal species consisted of alfalfa hay and concentrates with a forage/concentrate ratio of 50/50. The alfalfa hay and concentrates used were from the same batch throughout the experimental period. The concentrate diet (g/kg) consisted of: maize grain, 360; barley grain, 360; soybean meal, 160; wheat middlings, 110; calcium phosphate, 15; common salt, 3; mineral and vitamins premix, 2. The mineral and vitamin premix contained (per kg as mixed): 150 g Ca, 100 g P, 100 g Na, 100 mg Co, 300 mg I, 5000 mg Fe, 10 000 mg Mn, 20 000 mg Zn, 100 000 mg Se, 5 000 000 IU retinol, 500 000 IU cholecalciferol and 15 000 mg α-tocopherol. The full experimental designs have been described in detail for sheep and goats in the studies of Tsiplakou et al. (Reference Tsiplakou, Chadio and Zervas2012a) and Tsiplakou et al. (Reference Tsiplakou, Chadio, Papadomichelakis and Zervas2012b) respectively.

Mammary tissue

Mammary tissue (MT) samples were taken by biopsy on the 30th and 60th experimental day, which correspond to 120 and 150 d in milk respectively, of each dietary treatment after the morning milking. Before the biopsy, the udder of the animals was shaved and cleaned, and local anesthesia was achieved by subcutaneous injection of 2 ml lidocaine hydrochloride (xylocaine 2%, AstraZeneca, Athens, Greece). A 2-mm incision was made to facilitate the insertion of the biopsy needle. Both biopsy samples were taken from the right mammary gland using a Bard Magnum® Biopsy instrument (BARD, Athens, Greece) in which the biopsy needle (14G) was adapted. The length of the sample notch was about 1.9 cm and approximately 15 mg tissue was collected from a depth of 3–5 cm. After the tissue samples were taken, a stapler (Leukoclip SD, Smith and Nephew, England) was used to close the wound and the site of sampling received a prophylactic treatment with a disinfecting powder (Terramycin, w/Polymyxin, Pfizer, Athens, Hellas, containing 33.812 mg oxytetracycline hydrochloride and 1.457 mg Polymyxin B sulfate as active ingredients) and then covered with spray (Oxyvet spray, Provet, Athens, Greece, containing 2.2 g oxytetracycline HCL). Immediately after the biopsy sampling, all animals received antibiotic prophylaxis with 5 ml of Terramycin Long Acting (Pfizer, Athens, Hellas, containing 217.40 mg oxytetracycline dihydrate).

Determination of transcript abundance using real-time RT-qPCR assay

Total RNA was isolated from 15 mg of MT using the Trizol reagent (Thermo Fisher Scientific, Waltham, Massachusetts, USA) according to the manufacturer's protocol. DNase treatment used DNase I (Promega, Madison, WI) at 37°C for 60 min to remove all traces of genomic DNA. The RNA integrity was evaluated with agarose gel (3%) after isolation and after DNase treatment of the samples. Discrete bands were monitored in all samples representing 28s and 18s ribosomal RNAs respectively, showing little or no RNA hydrolysis. Quantity of RNA was assessed using a NanoDrop ND-1000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA). First-strand cDNA was reverse transcribed from 2 μg of DNase-treated total RNA, using SuperScript II reverse transcriptase (Invitrogen, Carlsbad, CA), according to manufacturer's protocol. The resultant cDNA was diluted to a final volume of 100 μl, and SYBR green-labeled PCR fragments were amplified using gene-specific primers (online Supplementary Table S1) designed from the transcribed region of each gene using Primer Express 1.5 software (Applied Biosystems, Darmstadt, DE). Consensus primers were designed in order to amplify target-gene regions for both animals. RT-PCR reactions were performed on a Stratagene MX3005P real-time PCR using iTaq Fast SYBR Green Supermix with ROX (BioRad, Hercules, CA) at a final volume of 15 μl, gene-specific primers at a final concentration of 0.2 μm each and 1 μl of cDNA. PCR cycling started at 95°C for 10 min, followed by 40 cycles of 95°C for 15 s and 60°C for 1 min. The primer specificity and the formation of primer-dimers were monitored by dissociation curve analysis and agarose gel electrophoresis. The geometrical mean of the expression levels of RPS9 and UXT genes was used as internal standard (Bionaz and Loor, Reference Bionaz and Loor2007). Relative transcript levels of the gene of interest (X) were calculated as a ratio to the geometrical average of RPS9 and UXT (C), as $\lpar 1 + E\rpar ^{-\Delta C_t}$, where ΔCt was calculated as $\lpar {C_t^X -C_t^C } \rpar $. PCR efficiency (E) for each amplicon was calculated employing the linear regression method on the Log(Fluorescence) per cycle number data, using the LinRegPCR software (Ramakers et al., Reference Ramakers, Ruijter, Deprez and Moorman2003). While some studies have identified references genes for cow (Bionaz and Loor, Reference Bionaz and Loor2007) and goat (Bonnet et al., Reference Bonnet, Bernard, Bes and Leroux2013) MT during lactation there is scarce information, to the best of our knowledge, for sheep. So, based on the fact that the UXT has been proposed both in cows and goats as a stable reference gene for the MT during lactation (Bionaz and Loor, Reference Bionaz and Loor2007; Bonnet et al., Reference Bonnet, Bernard, Bes and Leroux2013) it was also used in the present study. Additionally, the UXT has been used as a reference gene in a study with sheep MT (Carcangiu et al., Reference Carcangiu, Mura, Daga, Luridiana, Bodano, Sanna, Diaz and Cosso2013). As the choice of RPS9 is concerned, it was done taking into account that it has been characterized also by high stability in the MT of cows (Bionaz and Loor, Reference Bionaz and Loor2007) while in goats, Finot et al. (Reference Finot, Guy-Marnet and Dessauge2011) concluded that in the choice of reference genes should be included at least one ribosomal protein gene.

Statistical analysis

The experimental data were analyzed using the SPSS statistical package (version 16.0) using a general linear model (GLM) for repeated measures analysis of variance (ANOVA) with dietary treatments (T) (FL70; FL100; FL130) and sampling time (S) as fixed effects and their interactions (T × S) according to the model:

$$Y_{ijk} = \mu + T_i + S_j + \lpar {T \times S} \rpar _{ij} + A_k + e_{ijk}$$

where Υijk is the dependent variable, μ the overall mean, Ti the effect of dietary treatment, Sj the effect of sampling time, (T × S)ij the interaction between dietary treatments and sampling time, Ak the animal's effect and eijk the residual error. Multiple comparisons were obtained using Tukey's test. Significance was set at P < 0.05.

Results and discussion

Underfeeding (FL70 compared with FL100) caused a significant reduction in the mRNA expression of STAT3 and BECN1 genes in MT at both sampling times and in the first sampling time, respectively, in goats (Table 1) and in the mRNA expression of CASPASE 8 and BECN1 genes in the first sampling time in sheep (Table 2). For completeness, the overall mean values for each dietary treatment (disregarding time) and for each time point (disregarding diet) are given in the online Supplementary Table S2. STAT3 was postulated as a death factor in differentiated mouse mammary epithelium (Chapman et al., Reference Chapman, Lourenco, Tonner, Flint, Selbert, Takeda, Akira, Clarke and Watson2000), thus, an upregulation of the mRNA expression of STAT3 gene has usually been observed during mammary involution in cows (Singh et al., Reference Singh, Davis, Dobson, Molenaar, Wheeler, Prosser, Farr, Oden, Swanson, Phyn, Hyndman, Wilson, Henderson and Stelwagen2008; Piantoni et al., Reference Piantoni, Wang, Drackley, Hurley and Loor2010) and sheep (Colitti and Farinacci, Reference Colitti and Farinacci2009). In agreement with our results in sheep, Ollier et al. (Reference Ollier, Robert-Granie, Bernard, Chilliard and Leroux2007) reported a significant decline in the mRNA expression of CASPASE8 and BECN1 genes in the MT of 48 h food-deprived goats at first stage of lactation. Moreover, Moyes et al. (Reference Moyes, Drackley, Morin, Rodriguez-Zas, Everts, Lewin and Loor2011) indicated that several genes associated with cell death, other than those included in this study, were downregulated in the MT of cows with negative energy balance during mid-lactation. Thus, it can be assumed that the downregulation in the expression of genes involved with the programed cell death (PCD), which was observed in the MT of FL70 animals, could be part of a molecular mechanism intended to maintain their milk production as much as possible. Indeed, the fact that the down regulation in the above genes was more intense (statistically significant) at the first sampling time (after 30 experimental days) might show that the molecular mechanisms cannot preserve the milk production when the animals consume a diet which covers 70% of their nutritional requirements for more than two months. A positive correlation between milk yield and mRNA expression of BECN1, CASPASE 8 and BAX genes in goats was found (Fig. 1). Moreover, the fact that the mRNA accumulation of both CASPASE8 and BECN1 genes was affected simultaneously in the MT of FL70 fed sheep, may indicate that apoptosis and autophagy can be exhibited simultaneously, pointing out a complex regulation of these pathways.

Table 1. The mean relative transcript accumulation of genes in goat mammary tissue of the three dietary treatments (FL70, FL100, FL130), at the two sampling times (30th and 60th experimental day). The units in the Table are arbitrary

Means with different superscript (a, b) in each row (between dietary treatments) for each gene differ significantly (P ≤ 0.05).

*P < 0.05, ** P < 0.01, and *** P < 0.00, NS, Non significant.

Table 2. The mean relative transcript accumulation of genes in sheep mammary tissue of the three dietary treatments (FL70, FL100, FL130), at the two sampling times (30th and 60th experimental day)

The units in the Table are arbitrary.

Means with different superscript (a, b) in each row (between dietary treatments) for each gene differ significantly (P ≤ 0.05).

*P < 0.05, ** P < 0.01, and *** P < 0.00, NS, Non significant.

Fig. 1. Pearson correlation between apoptotic genes in mammary tissue, milk yield and composition and blood hormones in sheep and goats.

On the contrary, significantly higher mRNA expression of CASPASE3 and CTSB genes in the MT of feed restricted cows, which were at 11 weeks of lactation, has been reported by Dessauge et al. (Reference Dessauge, Lollivier, Ponchon, Bruckmaier, Finot, Wiart, Cutullic, Disenhaus, Barbey and Boutinaud2011). Moreover, Nørgaard et al. (Reference Nørgaard, Sørensen, Theil, Sehested and Sejrsen2008) observed that the transcript level of CASPASE3 was not affected by a low feeding level in the MT of cows which were at approximately 9 months of lactation. No difference in the epithelial cell apoptosis between cows fed with either low or high energy density diets, when the animals were at 8 weeks postpartum, has been observed by Boutinaud et al. (Reference Boutinaud, Ben Chedly, Delamaire and Guinard-Flament2008). The different response of negative energy balance on the expression of genes related with the PCD between cows and small ruminants may be attributed to animal species differences and to the level and duration of feed restriction. In addition, in contrast to small ruminants, in cows there is a characteristic overlapping between periods of lactation and pregnancy which may affect mammary PCD in a completely different way. Besides, the high levels of pregnancy hormones stimulate the development of new secretory tissue which may oppose the stimuli for mammary involution initiated by milk stasis (Gajewska et al., Reference Gajewska, Zielniok and Motyl2013). Moreover, the elevated levels of sex steroids during pregnancy may also affect the MT autophagy in cows. Indeed, the high autophagy in bovine mammary epithelial cells, when they are cultured in fetal bovine serum-deficient media in the presence of E2 or P4 in vitro, suggests that these hormones additionally stimulate the induction of this process (Sobolewska et al., Reference Sobolewska, Gajewska, Zarzynska, Gajkowska and Motyl2009).

The regulation of autophagy in bovine mammary epithelial cells is affected also by a combination of factors including auto/paracrine apoptogenic peptides as well as lactogenic hormones (Motyl et al., Reference Motyl, Gajewska, Zarzynska, Sobolewska and Gajkowska2007; Boutinaud et al., Reference Boutinaud, Lollivier, Finot, Bruckmaier and Lacasse2012; Lollivier et al., Reference Lollivier, Lacasse, Angulo Arizala, Lamberton, Wiart, Portanguen, Bruckmaier and Boutinaud2015). It has been shown in sheep that the lactation stage itself has an effect on the expression of genes related with mammary proliferation and PCD (Colitti et al., 2009). Moreover, feeding a low energy-density diet to cows inhibits mammary cell proliferation at 8, but not at 16, week post partum (Nørgaard et al., Reference Nørgaard, Sørensen, Sørensen, Andersen and Sejrsen2005). Thus, the impact of low feeding level on mammary cell proliferation and apoptosis, further to the animal species differences, is probably dependent on the lactation stage as well.

The mRNA transcripts of STAT3 and CASPASE8 genes were significantly higher in the MT of overfed goats (FL130 vs. FL100) at the second sampling time (Table 1). These results show that prolonged consumption (more than 2 months) of a diet which covers 130% of goats' nutritional requirements causes a significant up regulation of the expression of genes involved in PCD. It has been reported that obesity (Ozcan et al., Reference Ozcan, Cao, Yilmaz, Lee, Iwakoshi, Ozdelen, Tuncman, Gorgun, Glimcher and Hotamisligil2004) enhances the endoplasmic reticulum stress in mice MT and, as a consequence, activation of apoptotic mechanisms (Lin et al., Reference Lin, Li, Yasumura, Cohen, Zhang, Panning, Shokat, Lavail and Walter2007). In accordance with our findings, Hennigar et al. (Reference Hennigar, Velasquez and Kelleher2015) found significantly higher CASPASE3 accumulation, determined by immunoblotting, in the MT of obese lactating mice. A significant increase in caspase activation and apoptosis in adipose tissue from both mice with diet-induced obesity and obese humans has also been observed (Alkhouri et al., Reference Alkhouri, Gornicka, Berk, Thapaliya, Dixon, Kashyap, Schauer and Feldstein2010; Pintus et al., Reference Pintus, Floris and Rufini2012). Thus, excess feed intake may impair respiratory capacity and prime cells for apoptosis, increasing cellular susceptibility to additional stress.

Overfeeding sheep (FL130 vs. FL100) had a completely different effect when compared with goats. Specifically, at the first sampling time, a significant decrease in the mRNA transcript accumulation of CASPASE8 and BECN1 genes in the MT of FL130 fed sheep, in comparison with the FL100, was observed (Table 2). This reduction in the expression of genes involved with PCD may be due to the significant rise in the mRNA expression of MMP2 gene which was also found (Table 2). It has been reported that MMP2 promotes endbud invasion into the stroma of MT by suppressing epithelial apoptosis (Wiseman et al., Reference Wiseman, Sternlicht, Lund, Alexander, Mott, Bissell, Soloway, Itohara and Werb2003). Moreover, the fact that the sheep of our study had higher body fat accumulation compared with the goats (documented in Tsiplakou et al., Reference Tsiplakou, Chadio and Zervas2012a, Reference Tsiplakou, Chadio, Papadomichelakis and Zervas2012b), might mean that their MT contained more adipose tissue which would result in increased leptin production. It has been shown that the plasma leptin response to feeding level is strongly dependent on body fatness (Daniel et al., Reference Daniel, Whitlock, Baker, Steele, Morrison, Keisler and Sartin2002). Indeed, the leptin concentration in blood plasma was higher in FL130 fed sheep (2.22 ng/ml) compared with goats (1.57 ng/ml) (Tsiplakou et al., Reference Tsiplakou, Chadio and Zervas2012a, Reference Tsiplakou, Chadio, Papadomichelakis and Zervas2012b). Obesity significantly increased mRNA expression of leptin in mice MT (Kamikawa et al., Reference Kamikawa, Ichii, Yamaji, Imao, Suzuki, Okamatsu-Ogura, Terao, Kon and Kimura2009). Thus, it was hypothesized that leptin could also participate in the control of mammary epithelial cell growth and survival. It has been shown that leptin up-regulates the expression factors which are associated with the extra-cellular matrix, induces the expression of anti-apoptotic genes and reduces the expression of apoptotic genes in human mammary epithelial cells (MCF-7) (Perera et al., Reference Perera, Chin, Duru and Camarillo2008).

In the MT of FL130 fed goats significantly higher mRNA expression levels of STAT3, BAX, CASPASE8 and BECN1 genes, compared with the FL70 ones, were found (Table 1). As mentioned earlier, obesity creates endoplasmic reticulum stress (Ozcan et al., Reference Ozcan, Cao, Yilmaz, Lee, Iwakoshi, Ozdelen, Tuncman, Gorgun, Glimcher and Hotamisligil2004) which may tip the phenotype toward cell death. In contrast, no significant changes in the expression of genes involved either in programed cell death or with the extracellular matrix components were observed in the MT of sheep fed either with FL130 or FL70 (Table 2). These findings indicate that in ruminant MT the regulation of genes involved with apoptosis, autophagy and remodeling is controlled by complex mechanisms which remain to be studied in depth. Moreover, once again these results may indicate differences in the molecular mechanisms governing the PCD between sheep and goats even under the same dietary treatments.

A discriminant analysis was applied to pooled data of relative gene expressions in order to investigate if the samples can be distinguished not only based on the dietary treatments but also on animal species (Fig. 2). Seven variables were entered to develop a model to discriminate the ninety-six samples of each case. The percentages of the samples that were classified into the correct group, according to the dietary treatment and animal species were 66.7%. Wilks' lambda was observed at 0.076 for Function 1 (P < 0.001) and 0.516 for Function 2 (P < 0.001) and the relative expressions of CASPASE8 and STAT3 were the variables that contributed the most.

Fig. 2. Discriminant plot separating the samples by the dietary treatments (FL70, FL100, FL130) and animal species (goat in red, sheep in blue).

In conclusion, the mRNA accumulation of selected genes (STAT3, BECN1 and CASPASE8), involved in either apoptosis or autophagy in sheep and goat MT, was significantly down-regulated in the FL130 fed animals compared with the FL100 ones. The FL130, compared with the FL100, induced apoptosis (by increasing mRNA expression of STAT3 and CASPASE8) in goats MT, while the opposite happened in the case of sheep (by reducing mRNA expression of BECN1 and CASPASE8). Inhibition of programed cell death (apoptosis and autophagy) in the MT of FL130 fed sheep compared with the FL100 one, was accompanied by an enhancement in the remodeling process, indicated by the increase of MMP2 transcripts. The FL130, compared with the FL70 had different impact in the mRNA accumulation of some genes involved with either programed cell death (apoptosis and autophagy) or remodeling in sheep and goat MT which underlines animal species differences, details of which remain to be elucidated. Finally, apoptosis and autophagy can be affected simultaneously by the feeding level indicating complex molecular mechanisms linking the respective processes.

Supplementary material

The supplementary material for this article can be found at https://doi.org/10.1017/S002202992000103X.

Author contributions

Dr E. Tsiplakou designed the study, wrote the paper and performed the analyses. Both Dr G. Karalias and D. Skliros were involved in the laboratory analyses. Dr E. Flemetakis participated in writing and in the interpretation of the results.

References

Aits, S, Kricker, J, Liu, B, Ellegaard, AM, Hämälistö, S, Tvingsholm, S, Corcelle-Termeau, E, Høgh, S, Farkas, T, Holm Jonassen, A, Gromova, I, Mortensen, M and Jäättelä, M (2015) Sensitive detection of lysosomal membrane permeabilization by lysosomal galectin puncta assay. Autophagy 11, 14081424.CrossRefGoogle ScholarPubMed
Alkhouri, N, Gornicka, A, Berk, MP, Thapaliya, S, Dixon, LJ, Kashyap, S, Schauer, PR and Feldstein, AE (2010) Adipocyte apoptosis, a link between obesity, insulin resistance, and hepatic steatosis. The Journal of Biological Chemistry 285, 34283438.10.1074/jbc.M109.074252CrossRefGoogle ScholarPubMed
Bionaz, M and Loor, JJ (2007) Identification of reference genes for quantitative real-time PCR in the bovine mammary gland during the lactation cycle. Physiological Genomics 29, 312319.CrossRefGoogle ScholarPubMed
Bonnet, M, Bernard, L, Bes, S and Leroux, C (2013) Selection of reference genes for quantitative real- time PCR normalization in adipose tissue, muscle, liver and mammary gland from ruminants. Animal: An International Journal of Animal Bioscience 7, 13441353.CrossRefGoogle Scholar
Boutinaud, M, Ben Chedly, MH, Delamaire, E and Guinard-Flament, J (2008) Milking and feed restriction regulate transcripts of mammary epithelial cells purified from milk. Journal of Dairy Science 91, 988998.CrossRefGoogle ScholarPubMed
Boutinaud, M, Lollivier, V, Finot, L, Bruckmaier, RM and Lacasse, P (2012) Mammary cell activity and turnover in dairy cows treated with the prolactin-release inhibitor quinagolide and milked once daily. Journal of Dairy Science 95, 177187.CrossRefGoogle ScholarPubMed
Boya, P and Kroemer, G (2008) Lysosomal membrane permeabilization in cell death. Oncogene 27, 64346451.CrossRefGoogle ScholarPubMed
Capuco, AV, Wood, D, Baldwin, R, McLeod, K and Paape, M (2001) Mammary cell number, proliferation, and apoptosis during a bovine lactation: relation to milk production and effect of bST. Journal of Dairy Science 84, 21772187.CrossRefGoogle ScholarPubMed
Capuco, AV, Ellis, SE, Hale, SA, Long, E, Erdman, RA, Zhao, X and Paape, MJ (2003) Lactation persistency: insights from mammary cell proliferation studies. Journal of Animal Science 81, 1831.CrossRefGoogle ScholarPubMed
Carcangiu, V, Mura, MC, Daga, C, Luridiana, S, Bodano, S, Sanna, GA, Diaz, ML and Cosso, G (2013) Association between SREBP-1 gene expression in mammary gland and milk fat yield in Sarda breed sheep. Meta Gene 1, 4349.CrossRefGoogle ScholarPubMed
Chapman, RS, Lourenco, P, Tonner, E, Flint, D, Selbert, S, Takeda, K, Akira, S, Clarke, AR and Watson, CJ (2000) The role of Stat3 in apoptosis and mammary gland involution. Conditional deletion of Stat3. Advances in Experimental Medicine and Biology 480, 129138.CrossRefGoogle ScholarPubMed
Colitti, M and Farinacci, M (2009) Cell turnover and gene activities in sheep mammary glands prior to lambing to involution. Tissue and Cell 41, 326333.CrossRefGoogle ScholarPubMed
Colitti, M, Stradaioli, G and Stefanon, B (2005) Mammary cell turnover in lactating sheep is modulated by changes of energy fuels. Research in Veterinary Science 78, 53569.CrossRefGoogle ScholarPubMed
Daniel, JA, Whitlock, BK, Baker, JA, Steele, B, Morrison, CD, Keisler, J and Sartin, JL (2002) Effect of body fat mass and nutritional status on 24-hour leptin profiles in sheep. Journal of Animal Science 80, 10831089.CrossRefGoogle Scholar
Dessauge, F, Lollivier, V, Ponchon, B, Bruckmaier, R, Finot, L, Wiart, S, Cutullic, E, Disenhaus, C, Barbey, S and Boutinaud, M (2011) Effects of nutrient restriction on mammary cell turnover and mammary gland remodeling in lactating dairy cows. Journal of Dairy Science 94, 46234635.CrossRefGoogle ScholarPubMed
Finot, L, Guy-Marnet, P and Dessauge, F (2011) Reference gene selection for quantitative real-time PCR normalization: application in the caprine mammary gland. Small Ruminant Research 95, 2026.CrossRefGoogle Scholar
Gajewska, M, Gajkowska, B and Motyl, T (2005) Apoptosis and autophagy induced by TGF-B1 in bovine mammary epithelial BME-UV-1 cells. Journal of Physiology and Pharmacology 56, 143157.Google ScholarPubMed
Gajewska, M, Zielniok, K and Motyl, T (2013) Autophagy in development and remodelling of mammary gland. In Bailly Y (ed) Autophagy – a double-edged sword. Chapter 20. InTech Open, London.CrossRefGoogle Scholar
Green, KA and Lund, LR (2005) ECM degrading proteases and tissue remodeling in the mammary gland. Bioassays 27, 894903.CrossRefGoogle Scholar
Hennigar, SR, Velasquez, V and Kelleher, SL (2015) Obesity-induced inflammation is associated with alterations in subcellular zinc pools and premature mammary gland involution in lactating mice. The Journal of Nutrition Biochemical, Molecular and Genetic Mechanisms 145, 19992005.Google ScholarPubMed
Kamikawa, A, Ichii, O, Yamaji, D, Imao, T, Suzuki, C, Okamatsu-Ogura, Y, Terao, A, Kon, Y and Kimura, K (2009) Diet-induced obesity disrupts ductal development in the mammary glands of nonpregnant mice. Developmental Dynamics 238, 10921099.CrossRefGoogle ScholarPubMed
Knight, CH (2000) The importance of cell division in udder development and lactation. Livestock Production Science 66, 169176.CrossRefGoogle Scholar
Knight, CH and Peaker, M (1984) Mammary development and regression during lactation in goats in relation to milk secretion. Quarterly Journal of Experimental Physiology 69, 331338.CrossRefGoogle ScholarPubMed
Kreuzaler, PA, Staniszewska, AD, Li, W, Omidvar, N, Kedjouar, B, Turkson, J, Poli, V, Flavell, RA, Clarkson, RWE and Watson, CJ (2011) Stat3 controls lysosomal-mediated cell death in vivo. Nature Cell Biology 13, 303309.CrossRefGoogle ScholarPubMed
Lin, JH, Li, H, Yasumura, D, Cohen, HR, Zhang, C, Panning, B, Shokat, KM, Lavail, MM and Walter, P (2007) IRE1 Signaling affects cell fate during the unfolded protein response. Science (New York, N.Y.) 318, 944949.CrossRefGoogle ScholarPubMed
Lollivier, V, Lacasse, P, Angulo Arizala, J, Lamberton, P, Wiart, S, Portanguen, J, Bruckmaier, R and Boutinaud, M (2015) In vivo inhibition followed by exogenous supplementation demonstrates galactopoietics effects of prolactin on mammary tissue and milk production in dairy cows. Journal of Dairy Science 98, 87758787.CrossRefGoogle ScholarPubMed
Motyl, T, Gajewska, M, Zarzynska, J, Sobolewska, A and Gajkowska, B (2007) Regulation of autophagy in bovine mammary epithelial cells. Autophagy 3, 484486.CrossRefGoogle ScholarPubMed
Moyes, KM, Drackley, JK, Morin, DE, Rodriguez-Zas, SL, Everts, RE, Lewin, HA and Loor, JJ (2011) Predisposition of cows to mastitis in non-infected mammary glands: effects of dietary-induced negative energy balance during mid-lactation on immune-related genes. Functional Integrative Genomics 11, 151156.10.1007/s10142-010-0186-zCrossRefGoogle ScholarPubMed
National Research Council (1981) Effect of environment on nutrient requirements of domestic animals. Washington, DC: The National Academies Press.Google Scholar
Nørgaard, J, Sørensen, A, Sørensen, MT, Andersen, JB and Sejrsen, K (2005) Mammary cell turnover and enzyme activity in dairy cows: effects of milking frequency and diet energy density. Journal of Dairy Science 88, 975982.CrossRefGoogle ScholarPubMed
Nørgaard, JV, Sørensen, MT, Theil, PK, Sehested, J and Sejrsen, K (2008) Effect of pregnancy and feeding level on cell turnover and expression of related genes in the mammary tissue of lactating dairy cows. Animal: An International Journal of Animal Bioscience 2, 588594.CrossRefGoogle ScholarPubMed
Ollier, S, Robert-Granie, C, Bernard, L, Chilliard, Y and Leroux, C (2007) Mammary transcriptome analysis of food-deprived lactating goats highlights genes involved in milk secretion and programmed cell death. Journal of Nutrition 137, 560567.CrossRefGoogle ScholarPubMed
Ozcan, U, Cao, Q, Yilmaz, E, Lee, AH, Iwakoshi, NN, Ozdelen, E, Tuncman, G, Gorgun, C, Glimcher, LH and Hotamisligil, GS (2004) Endoplasmic reticulum stress links obesity, insulin action, and type 2 diabetes. Science (New York, N.Y.) 306, 457461.CrossRefGoogle ScholarPubMed
Perera, CN, Chin, HG, Duru, N and Camarillo, IG (2008) Leptin-regulated gene expression in MCF-7 breast cancer cells: mechanistic insights into leptin-regulated mammary tumor growth and progression. Journal of Endocrinology 199, 221233.CrossRefGoogle ScholarPubMed
Piantoni, P, Wang, P, Drackley, JK, Hurley, WL and Loor, JJ (2010) Expression of metabolic, tissue remodeling, oxidative stress and inflammatory pathways in mammary tissue during involution in lactating dairy cows. Bioinformatics and Biology Insights 4, 8597.CrossRefGoogle ScholarPubMed
Pintus, F, Floris, G and Rufini, A (2012) Nutrient availability links mitochondria, apoptosis and obesity. Aging 4, 734741.CrossRefGoogle ScholarPubMed
Ramakers, C, Ruijter, JM, Deprez, RH and Moorman, AF (2003) Assumption-free analysis of quantitative real-time polymerase chain reaction (PCR) data. Neuroscience Letters 339, 6266.CrossRefGoogle ScholarPubMed
Schorr, K, Li, M, Bar-Peled, U, Lewis, A, Heredia, A, Lewis, B, Knudson, CM, Korsmeyer, SJ, Jager, R, Weiher, H and Furth, PA (1999) Gain of Bcl-2 is more potent than bax loss in regulating mammary epithelial cell survival in vivo. Cancer Research 59, 25412545.Google ScholarPubMed
Sigl, T, Meyer, HHD and Wiedemann, S (2008) Gene expression analysis of protein synthesis pathways in bovine mammary epithelial cells purified from milk during lactation and short-term restricted feeding. Journal of Animal Physiology and Animal Nutrition 98, 8495.CrossRefGoogle Scholar
Singh, K, Davis, SR, Dobson, JM, Molenaar, AJ, Wheeler, TT, Prosser, CG, Farr, VC, Oden, K, Swanson, KM, Phyn, CV, Hyndman, DL, Wilson, T, Henderson, HV and Stelwagen, K (2008) cDNA microarray analysis reveals that antioxidant and immune genes are upregulated during involution of the bovine mammary gland. Journal of Dairy Science 91, 22362246.CrossRefGoogle ScholarPubMed
Sobolewska, A, Gajewska, M, Zarzynska, J, Gajkowska, B and Motyl, T (2009) IGF-I, EGF and sex steroids regulate autophagy in bovine mammary epithelial cells via the mTOR pathway. European Journal of Cell Biology 88, 117130.10.1016/j.ejcb.2008.09.004CrossRefGoogle ScholarPubMed
Stefanon, B, Colitti, M, Gabai, G, Knight, CH and Wilde, CJ (2002) Mammary apoptosis and lactation persistency in dairy animals. Journal of Dairy Research 69, 3752.CrossRefGoogle ScholarPubMed
Tsiplakou, E, Chadio, S and Zervas, G (2012a) The effect of long term under- and over-feeding of sheep on milk and plasma fatty acids profile and on insulin and leptin concentrations. Journal of Dairy Research 79, 192200.CrossRefGoogle Scholar
Tsiplakou, E, Chadio, S, Papadomichelakis, G and Zervas, G (2012b) The effect of long term under and over- feeding on milk and plasma fatty acids profile and on insulin and leptin concentrations of goats. International Dairy Journal 24, 8792.CrossRefGoogle Scholar
Tucker, HA (1969) Factors affecting mammary gland cell numbers. Journal of Dairy Science 52, 720729.CrossRefGoogle ScholarPubMed
Wall, E and McFadden, T (2012) Regulation of mammary development as it relates to changes in milk production efficiency. In Chaiyabutr, N (ed.), Milk Production – An Up-to-Date Overview of Animal Nutrition, Management and Health. pp. 258288. InTech Open, London. doi: 10.5772/50777. Available at https://www.intechopen.com/books/milk-production-an-up-to-date-overview-of-animal-nutrition-management-and-health/regulation-of-mammary-development-as-it-relates-to-changes-in-milk-production-efficiency.Google Scholar
Walton, KD, Wagner, KU, Rucker, EB III, Shillingford, JM, Miyoshi, K and Hennighausen, L (2001) Conditional deletion of the bcl-x gene from mouse mammary epithelium results in accelerated apoptosis during involution but does not compromise cell function during lactation. Mechanisms of Development 109, 281293.CrossRefGoogle Scholar
Wiseman, BS, Sternlicht, MD, Lund, LR, Alexander, CM, Mott, J, Bissell, MJ, Soloway, P, Itohara, S and Werb, Z (2003) Site-specific inductive and inhibitory activities of MMP-2 and MMP-3 orchestrate mammary gland branching morphogenesis. Journal of Cell Biology 162, 11231133.CrossRefGoogle ScholarPubMed
Yart, L, Lollivier, V, Finot, L, Dupont, J, Wiart, S, Boutinaud, M, Marnet, PG and Dessauge, F (2013) Changes in mammary secretory tissue during lactation in ovariectomized dairy cows. Steroids 78, 973981.CrossRefGoogle ScholarPubMed
Zervas, G, (2007) Ratio formulation for farm animals. Stamoulis Press, Athens.Google Scholar
Figure 0

Table 1. The mean relative transcript accumulation of genes in goat mammary tissue of the three dietary treatments (FL70, FL100, FL130), at the two sampling times (30th and 60th experimental day). The units in the Table are arbitrary

Figure 1

Table 2. The mean relative transcript accumulation of genes in sheep mammary tissue of the three dietary treatments (FL70, FL100, FL130), at the two sampling times (30th and 60th experimental day)

Figure 2

Fig. 1. Pearson correlation between apoptotic genes in mammary tissue, milk yield and composition and blood hormones in sheep and goats.

Figure 3

Fig. 2. Discriminant plot separating the samples by the dietary treatments (FL70, FL100, FL130) and animal species (goat in red, sheep in blue).

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