Transcriptional Changes Underlying the Secretory Activation Phase of Mammary Gland Development

Matthew J. Naylor1, Samantha R. Oakes1, Margaret Gardiner-Garden, Jessica Harris, Katrina Blazek, Timothy W. C. Ho, Foo C. Li, David Wynick, Ameae M. Walker and Christopher J. Ormandy

Development Group (M.J.N., S.R.O., M.G.-G., J.H., K.B., C.J.O.), Cancer Research Program, Garvan Institute of Medical Research, St. Vincent’s Hospital, Sydney, New South Wales 2010, Australia; Division of Biomedical Sciences (T.W.C.H., A.M.W.), University of California, Riverside, California 92521; and University Research Centre Neuroendocrinology (F.C.L., D.W.), Bristol University, Bristol BS2 8HW, United Kingdom

Address all correspondence and requests for reprints to: Christopher J. Ormandy, Development Group, Cancer Research Program, Garvan Institute of Medical Research, St. Vincent’s Hospital, Sydney, New South Wales 2010, Australia. E-mail: c.ormandy{at}garvan.org.au.


    ABSTRACT
 TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
The secretory activation stage of mammary gland development occurs after parturition and converts inactive lobuloalveoli to active milk secretion. This process is triggered by progestin withdrawal and depends upon augmented prolactin (Prl) signaling. Little is known about the Prl-induced transcriptional changes that occur in the mammary gland to drive this process. To examine changes in the mammary transcriptome responsible for secretory activation, we have used transcript profiling of three mouse models that exhibit failure of secretory activation: knockout of galanin (a regulator of pituitary Prl production and a mammary cell autonomous modulator of Prl action); treatment with S179D Prl (a phosphoprolactin mimic); and knockout of a single Prl receptor allele. A significant reduction in expression was observed in genes belonging to 46 gene ontologies including those representing milk proteins, metabolism, lipid, cholesterol and fatty acid biosynthetic enzymes, immune response, and key transcription factors. A set of 35 genes, commonly regulated in all three models, was identified and their role in lactogenesis was validated by examining their expression in response to Prl stimulation or signal transducer and activator of transcription 5 knockdown in the HC11 mouse mammary cell culture model. The transcript profiles provided by these experiments identify 35 key genes (many for the first time) involved in the secretory activation phase of mammary gland development, show that S179D acts as an antagonist of Prl action, and provide insight into the partial penetrance of failed lactation in Prl receptor heterozygous females.


    INTRODUCTION
 TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
UNLIKE MOST DEVELOPMENTAL processes, mammary gland development occurs after birth and in discrete phases dependent on the endocrine state of the organism. These phases have been defined as 1) ductal morphogenesis, occurring during puberty and with each estrous cycle; 2) alveolar morphogenesis, occurring during pregnancy and consisting of an initial proliferation phase, followed by the secretory initiation phase and secretory activation phase, 3) lactation postpartum, and then 4) involution during weaning of the offspring (1, 2).

Proliferative alveolar morphogenesis occurs in response to increased levels of estrogen, progesterone, and prolactin (Prl). An early increase in ductal side branching gives way to the formation of lobuolalveloar structures. During this phase the basic architecture of the gland is established, with lobuloalveoli replacing the previously predominant adipose tissue. The appearance of cytoplasmic lipid droplets signals the onset of lactogenesis, which is divided into the secretory initiation and activation phases (2).

The initiation phase, beginning around midpregnancy, results in the acquisition of limited secretory capacity. Milk protein gene expression commences in a programmed pattern such that Wdnm1 is expressed first, followed by the caseins, whey acidic protein (Wap) and lactalbumin (3). Secretory capacity is gained only by a subset of epithelial cells. Prl, progesterone, and estrogen are permissive for this stage of development, and further development is held in check by high progesterone levels controlled by the placenta (4). This occurs directly in humans via placental progesterone secretion or indirectly in mice via placental lactogen support of the progesterone-producing ovarian corpus luteum.

The secretory activation phase of lactation is triggered by falling progesterone levels, which in mice also trigger parturition, with the result that milk is immediately available to the pups. In humans, secretory activation commences after parturition and so lactation is delayed until 1 d or 2 d postpartum. Prl levels also rise in all species at this time and are essential for lactation (2). The mammary epithelium also synthesizes Prl, which is essential for the increase in epithelial cell proliferation that accompanies secretory activation (5).

Although the hormonal control of the concomitant morphological and functional events of secretory activation have been well described, the underlying alterations occurring in gene expression in the mammary gland that drive these events are not well understood. Experimental models used to examine secretory activation have been limited to the examination of the response of candidate genes to hormonal manipulation of whole animals. The combination of mouse gene knockout and microarray technology (6) now offers a new experimental approach to this question.

We have made two knockout models that experience failure of secretory activation. These are animals with a single functional Prl receptor (Prlr) allele (7) and animals in which the neuropeptide galanin (Gal) is lost (8). Loss of a Prlr allele reduces mammary Prlr expression during pregnancy (9) and, intriguingly, also results in poor maternal behavior, reducing or abolishing milk delivery to the pups (10). Gal is an autocrine/paracrine growth factor for the Prl-secreting pituitary lactotroph cells (8, 11) and, consequently, Gal–/– mice display a failure of estrogen-induced lactotroph proliferation and reduced Prl serum levels. As a result, secretory activation fails in Gal–/– mothers and the pups die (12). The levels of other pituitary hormones, such as GH, LH, FSH, and TSH are normal in Gal–/– mice. Gal and its receptors are also expressed by the mammary epithelium and we have recently demonstrated that Gal exerts a direct developmental effect via the mammary epithelium to modulate Prl action during pregnancy (13).

Several posttranslational modifications of Prl are known to occur (14) with phosphorylation of Prl being quantitatively the most important (15, 16, 17). This phosphorylation can be mimicked by mutation of the normally phosphorylated serine to an aspartate (S179D in most species). Treatment of female rats with S179D resulted in failed lactation and slower onset of maternal behavior (18, 19). The in vitro mechanism of S179D action is currently controversial, with both weak agonist and potent antagonist activities described (20, 21, 22, 23). In vivo treatment with S179D mimics a number of phenotypes previously described in Prlr–/– mice (10, 19, 24, 25, 26). For the purposes of the current study, S179D provides another model of failed secretory activation. Unlike the knockouts, its effects are exerted from the onset of pregnancy, providing a control for any undiscovered prepregnancy developmental effects in the germline models.

We used these experimental models combined with oligonucleotide arrays (Affymetrix, Santa Clara, CA; U74A2 GeneChip) to examine the alterations in the mammary gland transcriptome that result in secretory activation of the mammary gland.


    RESULTS
 TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
A Molecular Mimic of Phosphorylated Prl (P-Prl) Inhibits Secretory Activation
Serine 179 is the major phosphorylation site of human Prl (27, 28), and substitution of this position with aspartate (S179D) mimics the effects of P-Prl (21). We treated mice using 28-d miniosmotic pumps loaded with S179D, unmodified Prl (U-Prl), or vehicle (saline) inserted interscapularly on the day of observation of a vaginal plug after copulation. Of 15 saline-treated control animals who became pregnant, all had normal pregnancies and deliveries, and all successfully suckled a total of 120 pups, as indicated by the presence of milk in the stomach of the pups (Fig. 1AGo). Treatment of Gal+/+ animals with S179D caused lactational failure in four of five females and, despite continued suckling, the stomachs of 30 pups from these four S179D-treated mice did not contain milk. Significantly, treatment of five Gal–/– females with S179D, at rates that produced the lactational failure in Gal+/+ animals, was unable to rescue lactation, and all 40 pups showed no milk in their stomachs, demonstrating no agonist activity of S179D in this assay. S179D treatment prevented the large rise in the level of ß-casein gene expression seen in Gal+/+ animals (Fig. 1BGo). Levels in S179D-treated animals were comparable to those measured in Gal–/– animals and Prlr+/– animals, indicating that all models passed through secretory initiation but were developmentally blocked during the secretory activation phase. A reduction in expression in response to S179D was also seen in Wdnm1 and Wap milk protein mRNAs (Fig. 1CGo) and {alpha}- and ß-casein by Western blot (Fig. 1DGo). The comparison of milk protein content by Western analysis is complicated by the retention of colostrum in the S179D, Gal–/–, and Prlr+/– animals and its expulsion in the wild-type control animals capable of lactation in response to suckling. Colostrum has 5 times the milk protein content of milk and is seen as the strong pink staining of luminal content by hematoxylin and eosin histology in the S179D-treated glands. Morphological examination of the fourth mammary gland at the first day postpartum also showed that S179D treatment produced a block in development at the same developmental stage as that caused by loss of a Prlr allele (29) or loss of Gal (13). Compared with controls (Fig. 1EGo), lobules had formed, but appeared smaller and less dense than those seen in wild-type animals (Fig. 1FGo). Histological examination showed that, compared with vehicle-treated controls (Fig. 1GGo), the S179D-treated animals showed reduced alveolar density and failedlactation, seen as the pink-stained accumulation of colostrum protein within the ducts and alveoli of Fig. 1HGo. Together these data show that secretory activation had failed in S179D-treated animals.



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Fig. 1. S179D Inhibits Lobuloalveolar Development and Lactation in Mice

A, Percentage of mothers with surviving pups after treatment with vehicle (saline), U-Prl, or S179D of Gal+/+ or Gal–/– mice throughout pregnancy by 21-d miniosmotic pump. B, ß-Casein mRNA levels in the fourth inguinal mammary glands from Gal+/+ or Gal–/– mice measured by QPCR and expressed as a ratio of Gal+/+ levels at the first day postpartum. Comparison is made with levels seen in Prlr+/– mice incapable of lactation. C, Examination of the effects of S179D treatment on Wdnm1 and Wap expression by QPCR at the first day postpartum. Fold difference in expression levels expressed as S179D Prl-treated Gal+/+ mice vs. vehicle-treated Gal+/+ mice. D, Measurement of milk protein level ({alpha}-casein, ß-casein, and Wap) by Western blot and densitometry in S179D-treated Gal+/+ mice. E and F, Carmine-stained whole-mount analysis of mammary gland development in vehicle or S179D-treated Gal+/+ mice at the first day postpartum. G and H, Hematoxylin and eosin-stained 5-µm sections from the same glands.

 
S179D Prl Inhibits Signal Transducer and Activator of Transcription 5 (Stat5) Activation in the Mammary Gland
Binding of Prl to the Prlr results in receptor dimerization and subsequent activation of the Jak/Stat pathway (30), the major signaling pathway used by the long Prlr. Both Jak2 and Stat5 have been demonstrated as essential for mammary gland development and milk protein gene expression (31, 32). Activation of Prlr can also result in the induction of the Mapk and phosphatidylinositol 3 (PI3) kinase signaling pathways (33, 34, 35, 36). To investigate the mechanism of S179D-induced failure of lobuloalveolar development and lactation, the activation of these signaling pathways in the mammary gland was examined by Western blot.

The proportions of Stat5a in total protein were equal in the mammary glands of saline- and S179D-treated Gal+/+ mice; however, the amount of Stat5 that was phosphorylated was markedly reduced in the mammary glands of mice treated with S179D (Fig. 2AGo). The levels of phosphorylated and total ERK were variable among animal samples, and there was no apparent difference (Fig. 2BGo). Likewise, the amount of total and phosphorylated Akt, a downstream target of the PI3 kinase-signaling pathway, did not significantly change between the two groups of mice (Fig. 2BGo). A small diminution in the level of cyclin D1, previously reported to be up-regulated by U-Prl and down-regulated by S179D (20), was detected in some experiments.



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Fig. 2. S179D Prl inhibits STAT5 Activation in the Mammary Gland

Western analysis of STAT5 (A), and MAPK and PI3 kinase (B) signaling pathways in the mammary glands of saline-vehicle and S179D-treated Gal+/+ mice at the first day postpartum. C, The same analysis conducted using mammary glands from Prlr+/+ and Prlr+/– animals that exhibited no lactation (No lact.) or lactation sufficient for pup survival (Partial lact.).

 
Prlr+/– Show Diminished Stat5 Activation
We undertook the same comparison of signaling pathways in Prlr+/– mice. About two thirds of these animals experience failure of lactogenesis (NL) during late pregnancy (29), due to a reduction in Prlr numbers (37) and thus the level of Prlr signaling. These animals provide a second model of developmental arrest during the secretory activation phase. The Prlr+/– phenotype is partially penetrant and thus dependent upon the presence or absence of allelic variants or haplotypes that segregate in the mixed genetic background. Some individuals are able to lactate (L) at a level sufficient for pup survival. Comparison of Prlr+/– animals that experienced failure of secretory activation with Prlr+/+ animals showed a reduction in Stat5 phosphorylation, with no detectable alteration in the other pathways examined (Fig. 2CGo). Variable levels of Stat5 phosphorylation were seen in Prlr+/– animals capable of lactation sufficient for pup survival, but these were all higher than in the animals that could not lactate. We have previously shown mammary Stat5 phosphorylation in response to Gal in culture (13).

Investigation of the Altered Patterns of Gene Expression Underlying Failed Lactogenesis Produced by Loss of Gal, by Loss of a Prlr Allele, or by Treatment with S179D
We measured the alterations in gene expression during the secretory activation phase of lactogenesis using oligonucleotide expression arrays to compare the global patterns of altered gene expression in our three models of failed lactogenesis: loss of a Prlr allele, loss of Gal, and by treatment with S179D. To perform these experiments, RNA was pooled from four to six replicate animals from each of the seven different genotypes or treatment groups, and expression profiles were obtained using MGU74Av2 Affymetrix GeneChips. The entire experiment, including all animal treatments and RNA pooling, was repeated at a later time to provide complete experimental duplication. The results are available as supplemental data published on The Endocrine Society’s Journals Online web site at http://mend.endojournals.org. To gain a broad overview of the functional groups contained within the set of genes exhibiting altered expression in association with failed lactation, we used OntoExpress (38) to identify gene ontologies with statistically significant overrepresentation in the set of genes showing altered expression associated with failed lactation. These ontologies are shown in supplemental Table 1 (published as supplemental data on The Endocrine Society’s Journals Online web site at http://mend.endojournals.org) where x denotes the significant overrepresentation of that ontology in one or more of the animal models used, and ontologies are organized into functional groups. Genes involved in cholesterol, sterol, fatty acid, and lipid biosynthesis, metabolism, and glycolysis are overrepresented. Interestingly, genes involved in immune responses are also overrepresented to a sufficient degree to be detected at this broad-overview level, probably indicative of successful preventative control of organisms with potential to cause mastitis, as we did not detect any cases of the infection. Other notable ontologies include the IGF-binding proteins, actin cytoskeleton, and arginine metabolic enzymes.

Venn Analysis of the Alterations in Gene Expression Patterns
We undertook a Venn analysis of gene expression among the models of failed lactation. We searched for genes that showed altered expression between Prlr+/+ and Prlr+/– (lactating or nonlactating) in both experimental replicates. We denoted this set as "–Prlr," the genes showing changed expression due to loss of the Prlr. Similarly, we compared Gal+/+ to Gal–/– and identified the genes changing expression due to loss of Gal, denoted "–Gal." We compared Gal+/+ treated with saline to Gal+/+ treated with S179D to identify genes that changed in response to S179D treatment denoted "+S179D." We then combined these sets in the Venn analysis shown in Fig. 3AGo. There were 7,278 probe sets that were not expressed in the mammary gland of the 12,488 probe sets on the chip. There were 939 probe sets that showed changed expression in at least one of the models from a total of 5210 probe sets with detectable expression. The Venn analysis shows the number of genes with increased (I) or decreased (D) expression in each subset. The squares below the Venn diagram show these data for the intersections of two sets, and the pattern of gene expression change for the 35 genes of the center intersection set can be found in Fig. 5Go. The false discovery rate for each set is indicated in brackets.



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Fig. 3. Transcript Profiling of Three Models of Failed Lactation

Global patterns of gene expression change were analyzed in 1 d postpartum mammary glands from mice experiencing lactational failure due to treatment with S179D (+S179D), loss of a Prlr allele (–Prlr), or loss of the Gal gene (–Gal). A, Venn diagram depicting the patterns of unique and overlapping changes in gene expression among the models of failed lactation. The number of genes showing increasing expression (I) and decreasing expression (D) is given for the unique sets within the Venn, and for the two-way intersections in the squares below the Venn. Estimate of the false discovery rate due to multiple testing is indicated in brackets. The identities, behavior, and postulated function of the 35 genes of the central set can be found in Fig. 5Go. B, Comparison of the change in gene expression measured by Affymetrix chip (duplicates) and QPCR (triplicates) for nine genes chosen at random from the central set of 35 genes. Both techniques showed high reproducibility. The I or D call was verified in all cases, and the magnitude of the fold change was generally smaller when measured by Affymetrix.

 


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Fig. 5. The Common Lactation Signature: The Identities, Behavior, and Postulated Function of the 35 Genes with Altered Expression in all Models of Lactation Failure

The 35 genes of the central Venn set are identified by their gene name, which should be used to retrieve their Unigene entry for more detail (http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=unigene). Relative gene expression level is shown in all of the experiments analyzed using a heat map (darker shading indicates higher expression), and the experiments are clustered using these genes. Groups of animals experiencing lactational failure are indicated by green or blue shading, and lactating groups are shaded pink or yellow, using the clustering in Fig. 7Go. The postulated function of these genes has been placed where possible in a biochemical scheme of a lactating mammary epithelial cell. Unplaced genes are Tparl, Cuta, Gbp3, and the expressed sequence tags (ESTs). PDH, Pyruvate dehydrogenase; Cyp51, cytochrome P450 family 51; NEFA, nonesterified fatty acid.

 
We estimated the false discovery rate due to multiple testing by first comparing identical experimental replicates (e.g. Prlr+/+ with Prlr+/+) to find genes with changed expression due to random events or experimental error, and then randomizing these sets to produce a three-set Venn diagram, recalculating the Venn analysis in this way 240 times (twice the number of possible combinations). The median false discovery rate of the 240 measurements for each subset is indicated in brackets. The most important outcome of this analysis was the demonstration that the sets outside the –Prlr set and its intersections with the –Gal and +S179D sets had such high false discovery rates that they could be considered as biologically irrelevant. These irrelevant sets correspond biologically to unique and non-Prl-mediated actions. The unique actions of Gal (set of 110 I and 18 D) and the unique actions of S179D (set of 42 I and 86 D) each contained 102 members erroneously placed there by the multiple testing error, an 80% error rate. Similarly, the intersection set of 29 contained a 30% error rate. This analysis indicated first that S179D has virtually no detectable off-target effects and second that Gal acts to influence mammary gland development predominantly via modulation of Prl action, at least at this point in development. Conversely, the false discovery rate was very low for all sets and intersection sets within the –Prlr set, showing these subsets to be of high biological relevance.

Prlr was clearly shown to be the dominant force in secretory activation, as loss of a Prlr allele resulted in 654 of the 939 changes detected, with a strong bias toward positive action. The expression of most of these genes (602) was not influenced by S179D, greatly limiting the role of S179D and P-Prl as global modulators of Prl action, but the fact that S179D induced failure of lactation demonstrated that it regulated key genes. Knockout of Gal regulated 109 genes in common with loss of a Prlr allele. This set is indicative of Gal control of pituitary Prl secretion (12) and Gal modulation of Prl action at the mammary epithelial cell (13).

Examination of the +S179D sets shows that S179D shares actions in common with –Gal and –Prlr (central set of 35 genes) and with Prl independent of Gal (set of 52 genes). Where +S179D exerted effects in common with –Prlr (87 genes comprised of sets containing 52 and 35 genes), the observed pattern overwhelmingly demonstrated S179D to be an antagonist of Prl action, as just three of these 87 genes increased with S179D treatment and loss of Prl signaling, whereas 84 responded to a loss of Prl signaling flux and treatment with S179D in a similar way.

Validation of Array Results by Quantitative RT-PCR (QPCR)
We used QPCR on the LightCycler platform to confirm the array results for the nine genes selected from the central set of 35. In all samples the Affymetrix increasing or decreasing calls were confirmed by QPCR, and overall it was apparent that the Affymetrix estimate of the magnitude of change was conservative. Both the Affymetrix and QPCR techniques gave highly reproducible and consistent results (Fig. 3BGo) as we have observed previously in other studies (13, 25, 39), allowing the use of the Affymetrix profiles as an accurate measure of gene expression level.

Comparison of Milk Protein Expression and Lipid Biosynthetic Enzymes among the Models of Failed Lactation
We compared the changes in the expression of a panel of milk proteins and lipid biosynthetic enzymes to determine whether the arrest in secretory activation had occurred at the same point in development among our models of failed lactation. We used the gene panels defined by Rudolph et al. (6) for the milk proteins (Fig. 4AGo) and lipid biosynthetic enzymes (Fig. 4BGo) in this analysis. It is clear from this comparison that all models have proceeded through secretory initiation as all models express all of the milk proteins including {alpha}-lactalbumin, the last of the milk proteins to be expressed (3). All express the lipid biosynthetic machinery required for the production of lipid droplets, consistent with the histology of these models. Strikingly, the reduction in expression of these genes compared with wild-type animals is very similar among the models, with the exception of casein-{delta}, which showed the most heterogeneous response among the models. Thus these models arrest development at very similar points during secretory activation.



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Fig. 4. Developmental Arrest Occurs at the Same Stage in All Models of Failed Lactogenesis

The expression of a panel of milk protein genes (A) and lipid biosynthesis genes (B) developed by Ruldolph et al. (6 ) was examined in the models of failed lactation. Results are expressed as a percentage of their wild-type controls in an analysis using epithelial-specific keratin 18 to normalize gene expression across groups. Gray bars indicate calls of decreasing expression, and the white bar a call of no change in expression by MAS5. All decreases in expression were statistically significant at P < 0.01.

 
Key Lactational Regulators Identified from the Intersection Set
The 35 genes (Venn Fig. 3AGo) that were commonly altered in the three models of lactational failure represent a small set of key genes involved in lactogenesis. This is a very stringent analysis and relaxation of the conditions by requiring, for example, a gene to be represented in just one of two experimental replicates, expands the central set to many hundreds of genes. Clustering using the small set of 35 unequivocally separated those animals able to lactate from those unable to lactate. Analysis of the function of these genes by extensive literature searches showed that most were involved in the metabolic processes underlying milk production, such as the synthesis of triacylglycerols and cholesterol from glucose, transport of fatty acids from the circulation, and lactose synthesis. Although this finding is not surprising, many of the genes contained in this set have not previously been implicated in lactogenesis and they are now placed within the lactation pathway for the first time (Fig. 5Go). We have presented these data in a functional scheme based upon extensive literature searching, together with a heat map to indicate expression pattern, to allow a succinct summary of the large amount of information on which this figure is based. Unigene names are used and Unigene should be used as the access point to the gene structure, full gene name, and aliases, and thus the Medline publication data used to construct this figure. The Discussion contains details of the more immediately interesting genes in this set.

Genes Associated with Partial Rescue of Lactation in Prlr+/– Mice
This data set also allowed us to examine the alterations in gene expression that occur between Prlr+/– females that could not lactate and those able to lactate sufficiently for pup survival. Here we are examining the ability of segregating genetic elements within mixed 129 genetic backgrounds to rescue lactation in some individuals. Using an analysis of the data by the robust multiarray average (RMA)/penalized T Statistic method, of the top 100 genes ranked on significance of their P value for changed expression between Prlr+/– animals that lactated compared with those that did not, an extraordinary 25% were found to play a role in the initiation of DNA replication (Fig. 6Go). These genes are presented according to their function in the assembly of the DNA replication machinery, adapted from the review of Bell and Dutta (41). In addition to these genes, a number of G2/M phase genes were also found. As demonstrated by the heat map, the expression levels of these genes were not only higher than nonlactating animals but were higher than wild-type animals as well. Thus, the most prominent feature of lactational rescue in these animals is abnormally high expression of genes involved in cell proliferation and mitosis.



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Fig. 6. Increased Mammary Cell Proliferation Is Associated with Partial Penetrence of Prlr+/– Lactational Failure

Comparison of mammary gene expression profiles between Prlr+/– that were capable (L) or incapable (NL) of lactation, and Prlr+/+ animals, revealed a predominant functional group of genes involved in the initiation of DNA synthesis and G2/M progression. The relative expression levels of these genes are shown in a heat map (darker indicates higher expression). Groups of animals experiencing lactational failure are indicated by green or blue shading, lactating groups are shaded pink or yellow, using the clustering in Fig. 7Go. Their functions are shown in a diagram depicting the assembly of the prereplicative and replicative complex adapted from Bell and Dutta (41 ), which should be consulted for further detail. The black lines represent the DNA and the colored shapes represent the various protein components of the complex. Proteins active at G2/M phase are shown in the box below, where binding partners are indicated by short black lines. Proteins named in red show increased expression in Prlr+/– animals capable of lactation over both Prlr+/– NL and Prlr+/+. dNTP, Deoxynucleotide triphosphate; rNTP, ribonucleoside triphosphates.

 
Analysis by Hierarchical Clustering
We used hierarchical clustering to examine the similarity in gene expression changes among our various samples. Initial clustering using the 939 genes with changed expression grouped the samples according to the genetic background of the sample, which varies between Gal and Prlr knockouts, obscuring the effect of genotype or treatment. The Prlr and Gal knockout models were made using chimera breeding partners derived from different 129 mouse strains, and gene expression changes due to this background difference were dominant over changes induced by genotype. We have previously demonstrated the dramatic effects of genetic background on mammary ductal patterning (42). To overcome this inherent problem, we identified a set of genes that showed a change in expression between the wild-type (+/+) animals of the different strains and removed them from the analysis. This reduced our set of genes with genotype-specific changes to 316, and clustering using this set now allowed the effect of genotype to emerge. Four clusters were found (Fig. 7Go). The wild-type animals of both strains now formed a cluster together. This cluster was closely related to a second cluster containing the Prlr+/– duplicates that were capable of lactation. Distant to these clusters were the Prlr+/– that did not lactate and a fourth cluster containing animals treated with S179D and the two Gal–/–. The Gal–/– mice treated with U-Prl were split, indicating that the U-Prl treatment was less effective in rescuing lactation in one of the treatment groups. It is clear from this analysis that the changed pattern of gene expression produced by S179D treatment far more closely resembles the pattern of change produced by loss of Gal than loss of Prlr.



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Fig. 7. –Gal and +S179D Models Show Very Similar Patterns of Transcriptional Change

Hierarchical clustering was used to draw a dendogram that clustered the separate experiments according to the similarities in their pattern of gene expression. A, Clustering using a set of 316 genes that changed in at least one of the models. Clusters of highly related experiments are colored. Clusters experiencing lactational failure are green or blue; lactating clusters are pink or yellow. Panel B, Clustering using those genes that changed in the –Prlr model. C, Clustering using the +S179D gene set. D, Clustering using the –Gal set. L, Lactation; NL, no lactation.

 
We then examined relatedness between these samples from the point of view of each of the Venn sets in Fig. 3Go. When we clustered using the genes that changed in the Prlr model (–Prlr), we again produced the same four clusters, but the effects of S179D and loss of Gal were less distinguishable than Prlr genotype (Fig. 7BGo). Using the +S179D gene set to cluster separated the Gal–/– and S179D-treated samples from the rest (Fig. 7CGo), and clustering using the –Gal set (Fig. 7DGo) split the wild type and Prlr+/– that could lactate from the S179D and Prlr+/– that experienced lactational failure. This analysis suggests a close relationship between the transcriptional changes caused by the loss of Gal and those caused by treatment with the S179D mimic of P-Prl. We investigated the P-Prl pituitary secretion of phosphoprolactin in Gal–/– vs. Gal+/+ mice.

The Ratio of Phosphorylated to Unphosphorylated Prl Is Altered in the Pituitaries of Gal–/– Mice
We sought to determine whether expression of Gal regulates the ratio of P-Prl to U-Prl that is released by the pituitary. To eliminate the effects of hormonal status on the degree of Prl phosphorylation, male animals were used. In Gal+/+ male mice, 80.0 ± 4.1% of Prl was present in the unmodified form, whereas 20.0 ± 1.9% was in the phosphorylated form (Fig. 8Go). Gal–/– mice, however, had 68.9 ± 3.2% of Prl as the unmodified form and 31.1 ± 2.1% as the phosphorylated form (Fig. 1Go, P < 0.0001 Student’s (unpaired) t test). Thus, the relative ratio of U-Prl to P-Prl was 4:1 in Gal+/+ mice, compared with 2:1 in Gal–/– mice (Fig. 8Go).



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Fig. 8. Levels of Modified Forms of Prl Secreted from the Pituitaries of Gal–/– and Gal+/+ Mice

Pituitaries were isolated from Gal+/+ and Gal–/– mice and incubated in media before analysis of the media for phosphorylated (P-Prl, P) and unmodified (U-Prl, U) forms of Prl by silver-stained two-dimensional gel electrophoresis. Gels were quantified by densitometry, and the proportion of U-Prl and P-Prl are expressed as a percentage ± SEM. P-Prl was 20 ± 1.9% in Gal+/+ and 31 ± 2.1% in Gal–/–, P < 0.0001 by Student’s t test, changing the ratio of P-Prl:U-Prl from 4:1 in Gal+/+ to 2:1 in Gal–/–.

 
Behavior of the Members of the Set of 35 Key Lactational Regulators Using the HC11 Mouse Mammary Cell Model
To examine the ability of Prl to directly regulate the expression of the 35 genes presented in Fig. 5Go, we used the HC11 mouse mammary cell line. These cells initially proliferate to confluent density under the influence of epidermal growth factor during the first 3 d of culture and then differentiate in response to Prl added at d 4 by forming domes and synthesizing ß-casein. Milk proteins, as an assay endpoint, are measured at d 8. We measured the expression level of the 35 genes using Affymetrix chips at d 2, d 3, d 4, and d 8. Of the 35 genes, we detected expression of 28, and their fold change in expression in response to Prl and the P value for this change are shown in Fig. 9AGo. Genes are named where they showed a significant P value for changed expression, or the case of Cidea and Angptl4 where they showed a large fold change but nonsignificant P value due to a low level of expression at the edge of detectability. The genes Slc39a8, Slc34a2, Car2, Aldo3, Kcnk1, Ctsc, Elovl5, and Ugalt, which showed decreased expression in the models of failed secretory activation, all showed increased expression in response to Prl in HC11 cells with significant P values. Psmb9 and the transcription factors Cebpd and Sox4, which showed increased expression in all models of failed secretory activation, showed decreased expression in response to Prl in HC11 cells. Four genes (Fdps, Acly, Gbp3, and Ctgf) showed the opposite pattern of regulation. Of the remaining 14 genes that were not directly regulated by Prl between d 4 and d 8, Erbb, Folr1, Sqle, Siat, G0s2, and Scd2 showed expression levels that increased from d 2 to d 4 and then reached a plateau, or dropped to zero (G0s2), indicating their regulation during the growth phase of these cells and confirming their role in the proliferative phase of mammary development.



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Fig. 9. Examination of the Expression of the 35 Genes Common to All Models of Failed Secretory Activation

A, The expression of the 35 genes identified in Fig. 5Go were measured in HC11 cells at 2 d, 3 d, 4 d, and 8 d using the experimental scheme outlined in Materials and Methods section. RNA from three independent experiments was pooled in equal ratios, and gene expression was measured using Affymetrix chips. Results are expressed as fold change relative to the expression level at d 4 (when Prl was added), and the P value for the gene expression change from d 4 to d 8 is indicated. B, siRNA was used to knock down expression of Stat5A in HC11 cells. Representative Western blot for Stat5A is shown in the top panel, with P value for the knockdown calculated from densitometric quantification of three independent experiments indicated in the bar graph. QPCR was used to measure the effect of the loss of Stat5 on the expression of the key lipogenic enzymes, Aldo3 and Scd2. GFP was used as a siRNA control, Stat5B was used as a specificity control, and the Stat5A-regulated milk proteins Wdnm1 and Csnb were used as positive controls. Results are expressed as fold change relative to GFP control and P values indicate statistically significant differences at d 4 for three independent experiments. Csnb was not expressed at d 4 but is significantly reduced at d 6 to d 8 (P = 0.05). NS, Nonsignificant (P = 0.3).

 
To examine the role of Stat5A we used short interfering RNA (siRNA) directed against Stat5A to reduce Stat5A expression. Cells were grown using the scheme outlined above but were transfected during the growth phase at d 2 with either the Stat5 siRNA or a siRNA directed against the green fluorescent protein (GFP), used as a control. Gene expression was measured at d 4, d 6, and d 8. Stat5A protein levels at d 4 were significantly (P = 0.014) reduced to 25% of levels seen in cells transfected with siRNA directed against GFP (Fig. 9BGo), but recovered over d 6 to d 8. We have observed a similar rapid recovery in HC11 cells with a number of other siRNAs, indicating this may be a general feature of these cells. The level of the highly homologous Stat5B protein remained unchanged, demonstrating the specificity of this approach. Reduction of Stat5 caused a fall in the levels of the milk proteins Wdnm-1 (P = 0.018, d 4; and P = 0.06, combined d 6 and d 8) and Csnb (no expression, d 4; and P = 0.05 for combined d 6 and d 8 data) demonstrating that we had reduced Stat5 levels sufficiently to have an effect on the expression of these Stat5-regulated genes. We chose to examine whether reduction of Stat5 could reduce the levels of key lipogenic enzymes Aldo3, the key step in the conversion of glucose to pyruvate, and Scd-2, the rate-limiting step in the production of acyl-Coenzyme As. Knockdown of Stat5 significantly reduced mRNA expression of both these enzymes at d 4 (Aldo3, P = 0.06; and Scd-2, P = 0.000016), and their mRNA levels recovered as Stat5 levels recovered, with no significant expression difference at d 6–d 8. These experiments show that key points in lipogenesis fall under the control of Stat5. Overall, these experiments with the HC11 cells show the existence of direct mechanistic links between Prl, Stat5, and the 35 genes identified as common to our three models of failed secretory activation. A large proportion of the genes identified in Fig. 5Go as key lactation genes fall under either the direct control of Prl or under the control of other regulatory processes during HC11 cell growth.


    DISCUSSION
 TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
We have compared three models of failed secretory activation in mice to define a small set of genes that display altered gene expression in all models, revealing a key set of genes involved in the initiation of lactation. This data set has also allowed us to gain insight into the mechanisms underlying the partially penetrant Prlr+/– phenotype and suggests a previously unknown mechanism of regulating Prl phosphorylation.

We have established a new mouse model of failure of secretory activation, using S179D Prl to inhibit this phase of mammary gland development. In experiments reported in Figs. 1Go, 2Go, and 4Go, S179D treatment during pregnancy reduced the expression of a broad range of genes involved in lactation, such as lipid and cholesterol synthesis enzymes, solute carriers, and lipid transport enzymes. Milk proteins were also dramatically reduced. Specifically, ß-casein mRNA showed a large decrease in expression in S179D Prl-treated mice compared with saline-treated mice (Figs. 1Go and 4Go). Analysis of milk protein levels also demonstrated a reduction (Fig. 1Go). Together these findings indicate that lactation failed due to a failure of differentiation. This conclusion is also supported by the observation that S179D treatment reduces Stat5 phosphorylation (Fig. 3Go).

These experiments are consistent with a study published during the course of these investigations in which Walker and colleagues (18) reported that S179D inhibited lactation in rats. In this report Walker and colleagues used Northern blotting of S179D-treated mouse mammary HC-11 cells to document a greater induction of ß-casein relative to the ribosomal subunits in response to S179D vs. U-Prl. Although it is initially tempting to directly contrast the induction of ß-casein by S179D in vitro with the repression observed in vivo, such a comparison involves the direct effect of S179D and U-Prl on the HC-11 ß-casein promoter in vitro compared with the developmental effects of S179D and U-Prl on a complex tissue in vivo, making conclusions difficult to draw. The basis of this inconsistency remains to be investigated but could be a consequence of altered short to long receptor ratios (18) or the high levels of insulin and/or hydrocortisone used in the in vitro system.

The in vitro antagonism of Prl action by S179D has been disputed by some (22, 23) and supported by others (20), indicating that in vitro the action of S179D remains to be fully explored. This is in stark contrast to the in vivo situation in which S179D reproduces a number of phenotypes seen in the Prlr knockout model (10, 19, 24, 25, 26), demonstrating a clear Prl antagonist activity. To examine this point, we used global gene expression as an endpoint to further analyze whether S179D acted as an agonist or as an antagonist of Prl-induced alterations in gene expression in our model of S179D-induced failure of lactogenesis. We compared the pattern of altered mammary gene expression caused by treatment with S179D to the alterations produced by the loss of a single Prlr allele, and to the alterations caused by the loss of Gal. All three models exhibit a phenotypically indistinguishable failure of lactogenesis. There were 87 genes (35 + 52) that showed altered expression in response to loss of a Prlr allele and treatment with S179D. Of these, 75 showed decreased expression and nine showed increased expression, in response to loss of a Prlr allele and treatment with S179D, a pattern demonstrating S179D as an antagonist of Prl action. Two genes showed increased expression with S179D, but decreased expression in response to the loss of a Prlr allele, and one gene showed the inverse pattern; both are patterns that indicate S179D was acting as a Prl agonist. Thus S179D is overwhelmingly acting as an antagonist of Prl action on lactogenesis but, at the level of the expression of specific genes, it has detectable agonist activity for three genes. This conclusion must also be viewed in the light of total Prl action. Overall, the loss of a Prlr allele affected the expression of 654 genes, of which just 87 (13%) were altered by S179D. Given the failure of lactogenesis in S179D-treated animals this 13% was clearly a functionally important subset of Prl-regulated genes, but this small subset indicates either that S179D is not a global antagonist of Prl action or that there are developmental effects of the absence of one Prlr allele that result in the disparity. Given the induced failure of lactation, it cannot be argued that this small subset simply results from a suboptimal dose of S179D resulting in submaximal U-Prl antagonism, or a partial agonist activity of S179D.

Another aspect of this comparison was the discovery of 128 genes that responded to S179D treatment, but not to loss of a Prlr allele or loss of Gal. This set contains a high false discovery rate (102), demonstrating that most of these genes are false positives. Thus S179D has a very restricted unique activity (off-target activity). The same caveat applies to the 128 (110 + 18) genes specific to the Gal–/– set that could represent a direct action of Gal that is independent of Prl action, if not for the high false discovery rate. This indicates this effect is small and that almost all of Gal action during secretory activation is via modulation of Prl action by 1) control of serum Prl levels (12), 2) Gal modulation of Prl action at the mammary epithelial cell (13), and 3) possibly also via regulation of Prl phosphorylation (Fig. 8Go). It is during the transition from the proliferative to secretory initiation phase at midpregnancy that Gal serum levels and mammary Gal receptors are at their highest, conditions most suitable for direct Gal action independent of Prl (13).

To further examine the similarity between the effects of S179D, the loss of Gal, and the loss of a Prlr allele we examined our profiles using hierarchical clustering to group them based on the similarity of changes in their transcript profiles. Whereas the Venn analysis was based on a change in gene expression among our models of failed lactation irrespective of magnitude, hierarchical clustering groups experimental replicates together based upon the level of gene expression, allowing an estimate of overall similarity between expression profiles from their relative position in the computed dendogram. We also used principal-components analysis to cluster the experimental replicates, with very similar results to those found with hierarchical clustering. Gal–/– and S179D-treated glands consistently fell within the same cluster. This approach showed that the pattern of gene expression found in glands experiencing lactational failure due to S179D treatment was very similar to the pattern seen in nonlactating glands from Gal–/– mice and that both were distant from the pattern of gene expression seen in nonlactating Prlr+/– mice. This suggested that alteration in the ratio of U-Prl to P-Prl may form part of Gal’s modulation of lactogenesis.

A functional analysis of the 35 genes common to all three models of failed lactation was undertaken by extensive literature searches, allowing almost all of these genes to be placed in the model of a lactating mammary epithelial cell presented in Fig. 6Go. This analysis implicated a number of genes in lactation for the first time. Examples include Cidea, a key metabolic gene (43), and the ubiquitin-like Isg15, which is known to prolong the activity of Stat family members by conjugation (44). The key transcription factors Srebf1, controlling lipid metabolism genes (45), Cebp{delta}, involved in lipogenic responses and mammary development (46), and Sox4, a progesterone-responsive transcription factor (47), were also found in this set. The latter two transcription factors were expressed at a higher level in nonlactating animals, and our results suggest that their loss of expression is required for secretory activation. Other genes showing this pattern included Erbb3, two probe sets interrogating Angptl4 expression, which is an inhibitor of lipoprotein lipase (48), proangiogenic Ctgf (49), and antiangiogenic Thbs1 (50). A large number of genes have been implicated in the process of secretory activation by a detailed time-course study using wild-type FVB mice (6), and a comparison of data sets will allow Prl-regulated genes to be distinguished from those regulated by the developmental process in general. We used the HC11 mammary epithelial cell model to show that a large proportion of these 35 genes were directly regulated by Prl, and we knocked down Stat5A expression to demonstrate that two key genes in de novo synthesis of lipids from glucose, Aldo3 and Scd2, were responsive to the levels of Stat5A expression, providing a further mechanistic link between our observations and the endocrine control of secretory activation.

Our data sets also allowed us to examine the changes in gene expression that resulted in lactation in Prlr+/– mice. We detected a very strong proliferation signal in lactating Prlr+/– mammary glands, with almost all of the genes involved in the initiation of DNA replication (41), and a number from the G2/M phase of the cell cycle, showing elevation in expression not only above nonlactating Prlr+/– glands but also above Prlr+/+ glands. Notable among this set was the elevated expression of proliferating cell nuclear antigen and Ki67, widely used markers of proliferation. Searching for a potential cause for this we found that epidermal growth factor (Egf) was 4-fold higher and ras family members Rab-18 and K-ras were 2-fold higher in lactating glands. As the Egf signaling pathway results in Stat5 phosphorylation, this provides a potential Prl-independent growth factor signal that could account for the increased levels of Stat5 phosphorylation seen in lactating Prlr+/– animals. Other genes found to be elevated in lactating Prlr+/– glands included many of the key lactational genes shown in Fig. 5Go. Another gene elevated in this group was synuclein-{gamma}, otherwise known as persyn or breast cancer-specific gene 1, the increased expression of which is associated with aggressive breast cancer, increased metastasis, and activation of estrogen-driven transcription (51). Interestingly, apoptosis genes were not prominent in this group.

In summary, treatment of mice with a molecular mimic of phosphorylated Prl resulted in failed lactation and impaired lobuloalveolar development that was associated with reduced Stat5 activation in the mammary gland. Transcriptome analysis of the secretory activation phase of mammary gland development using three models of failed lactation identified potential key regulatory genes for this process. Transcript profiling showed that S179D has actions that are predominantly, but not exclusively, antagonistic to U-Prl-regulated gene expression in the mammary gland. Increased cell proliferation was observed in Prlr+/– females able to lactate, providing mechanistic insight into the partial penetrance of this phenotype. Prl treatment of HC11 cells demonstrated that many of the 35 key genes were under direct Prl regulation and that others were associated with mammary epithelial cell proliferation. Stat5 mediated Aldo3 and Scd2, key enzymes in de novo lipid biosynthesis from glucose. Together these results provide a small list of key genes involved in secretory activation for which a number of applications can be envisaged. For example, these genes provide an excellent starting point for the identification of alleles that may provide enhanced lactational performance in a marker-assisted selection process in commercially valuable agricultural species. Alternatively, their study may help our understanding of lactation failure and other disorders of the breast.


    MATERIALS AND METHODS
 TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
Animals
All experiments involving mice were performed under the supervision and in accordance with the regulations of the Garvan/St Vincent’s Hospital Animal Experimental Ethics Committee. Gal–/– mice (12) were inbred on the 129OlaHsd genetic background. Prlr+/– mice (7) were of mixed 129SvPas/129OlaHsd genetic background. All animals were specific pathogen free and housed with food and water ad libitum with a 12-h light, 12-h dark cycle at 22 C and 80% relative humidity.

Two-Dimensional PAGE
Following decapitation the anterior pituitary was removed, cut into 1-mm pieces, rinsed in PBS to remove material from damaged cells, and incubated in DMEM containing 0.1% BSA for 2 h at 37 C in an atmosphere of water-saturated 5% CO2. At the end of the 2-h incubation period, the medium was removed and frozen before preparation for two-dimensional gel analysis. Two pituitaries were used per 2 ml of incubation medium to allow sufficient Prl accumulation in the samples from the Gal–/– mice. The proteins in the incubation medium were precipitated in 4 vol of –20 C acetone overnight, collected by centrifugation, and then dissolved in urea lysis buffer containing 9 M urea, 5% 2-mercaptoethanol, 4% ampholines (pH 4–6.5) (Sigma Chemical Co., St. Louis, MO). Electrophoresis was performed according to the method of Ho et al. (17). After electrophoresis the gel was silver stained (52), and the spots were identified by reference to standards as described previously (53) and by reference to a corun sample that was subject to Western blot analysis (53). Spot intensity was analyzed using a Kodak image analysis system (Eastman Kodak Co., Rochester, NY).

Phosphorylated and Unmodified Prl Treatment of Mice
On the morning of the observation of a vaginal plug, 6- to 8-wk-old mice were implanted with a 0.25 µl/h, 28-d Alzet miniosmotic pump (Alzet Osmotic Pumps Durect Corp., Cupertino, CA) containing either U-Prl or S179D, the molecular mimic of P-Prl; both hormones were prepared as described elsewhere (21). Either 0.6 or 1.2 µg was delivered per 24 h. On the first day postpartum, maternal behavior of mothers was observed, pups were examined for the presence of milk, and glands were taken for histological analysis.

Histological Analysis
Mammary whole mounts were made by spreading the gland on a glass slide before fixing in a 10% formalin solution. Glands were defatted in acetone before carmine alum (0.2% carmine, 0.5% aluminum sulfate) staining overnight. The whole mount was dehydrated using a graded ethanol series followed by xylene treatment for 60 min and storage and photography in methyl salicylate (54).

mRNA Isolation
The fourth inguinal mammary gland was frozen in liquid nitrogen before storage at –80 C before use. Total RNA was extracted using TRIZOL Reagent (Life Technologies, Gaithersburg, MD) according to the manufacturer’s instructions.

QPCR
QPCR was performed using LightCycler technology (Roche Clinical Laboratories, Indianapolis, IN). Primers were designed on the basis of mismatch to other genes. PCR reactions were performed in 10-µl volumes with 1 µl cDNA, 5 pmol of each primer, and FastStart DNA Master SYBR Green I enzyme mix (Roche) as per manufacturer’s instructions. Relative quantitation of the product was performed by comparing the crossing points of different samples normalized to an internal control (ß-actin). Each cycle in the linear phase of the reaction corresponds to a 2-fold difference in transcript levels between samples. Each reaction was performed in duplicate using pooled RNA from the three to six mammary glands per experiment.

mUgalt2 F a GGTGGTTGGAATAGAAGAGCACAC

mUgalt2 R a CAAGACCGAGACCCAGGAAAAC

mFolr1 F a TGGAGTTGGCGATTAGAGTCTGAC

mFolr1 R a GAGGCAGGTGTCTTGGATAAAGTG

mSiat1 F a TGTAAAATGGGGGTGACAATCC

mSiat1 R a CTCTTGCTGACCTCTTGAAGGAAC

mCyp51 F a AAAGGTAATGGGGTCGTGTAGTTG

mCyp51 R a GCACAGAATACGGGCAATGATAC

mCuta F a TGTCCCAACGAAAAAGTCGC

mCuta R a AAAGGCATCAGGAGCAGGAGAG

mCopz1 F a CAGCACAAGTGGGTTTGGAGTG

mCopz1 R a TGAGGAGAAGGAACACGGCAAG

mCsnd F a TATTACCCATCTACCCCCAGCC

mCsnd R a GAAACCCACAAGCAGACCTAACAC

mCsnb F a TTCACCTCCTCTCTTGTCCTCCAC

mCsnb R a GGGGCATCTGTTTGTGCTTG

mWDMN1 TGACAATGACTACTGCCTGGGC

mWDMN1 TTCCAAAACTGCGTGGGGGC

mWAP F a TGCCTCATCAGCCTCGTTCTTG

mWAP R a CTGGAGCATTCTATCTTCATTGGG

mCIDEA F a GACTTCCTCGGCTGTCTCAATG

mCIDEA R a GAAACTGATTCGTATCCACGCAG

mErbb3 F a TCTACCAAGTGGAACAGGAGAGGC

mErbb3 R a CACCAACAAACGGAGTCTGGAAG

mKeratin18 F a CAAGATCATCGAAGACCTGAGGGC

mKeratin18 R a TGTTCATAGTGGGCACGGATGTCC

mAldo3 F TGCCAGTATGTTACAGAGAAGGTCC

mAldo3 R CCGCTTGATAAACTCCTCAGTAGC

mScd2 F GCTGGGGCGAGACTTTTGTAAAC

mScd2 R TGGCTTCTGGAACAGGAACTGC

mStat5a F CACAGGTGGAAGATTGGGGTTC

mStat5a R CCACTCCCCATCCAAAAACC

mStat5b R CGAATGGAGAAAAGGGATGGTG

mStat5b F GTTCCTCTGCCAGGTAGTCCATAG

Western Analysis
Following RNA extraction from mammary glands using TRIZOL Reagent, protein was extracted according to the manufacturer’s instructions. Protein was separated using SDS-PAGE (Bio-Rad Laboratories, Hercules, CA), transferred to polyvinylidine difluoride (Millipore Corp., Bedford, MA), and blocked overnight with 2% fetal bovine serum, 50 mM sodium phosphate, 50 mM NaCl, and 0.1% Tween 20. Membranes were incubated with one of the following primary antibodies: {alpha}-milk protein (Accurate Chemical & Scientific Corp., Westbury, NY), {alpha}-Stat5A (Upstate Biotechnology, Inc., Lake Placid, NY), {alpha}-phospho-Stat5, {alpha}-phospho-Erk1/2, {alpha}-Erk2, {alpha}-phospho-Akt (S473), {alpha}-phospho-Akt (T308), {alpha}-Akt (Cell Signaling Technology, Beverly, MA) or {alpha}-ß-actin (Sigma). Protein (20 µg) was loaded per lane except for {alpha}-milk protein where 400 ng of protein was loaded. Specific binding was detected using horseradish peroxidase-conjugated secondary antibodies (Amersham Biosciences, Arlington Heights, IL) with Chemiluminescence Reagent (PerkinElmer, Norwalk, CT) and Biomax Light Film (Eastman Kodak).

Transcript Profiling
Total RNA was extracted using TRIZOL Reagent (Invitrogen Life Science, Carlsbad, CA), purified using RNeasy Mini Kit (QIAGEN, Chatsworth, CA); cDNA synthesis was performed using Superscript II (Invitrogen Life Technologies), and synthesis of biotin-labeled cRNA was performed using BioArray HighYield RNA Transcript labeling kit (Enzo Life Sciences, Farmingdale, NY) and hybridized to Affymetrix MGU74Av2 GeneChips overnight according to manufacturer’s instructions. Arrays were performed in duplicate using four to six glands per treatment group from two separate replicate experiments. Analysis was performed using the Affymetrix GeneChip version 5 software (MAS 5). Data were also analyzed as follows: Signal intensities of each gene were obtained using the RMA function in the Affy package in R (http://www.bioconductor.org). The RMA function, which involves quantile normalization of oligonucleotide signals followed by estimation of the average perfect match signal intensity for each probe set, has been shown to reduce variability and bias when compared with the MAS 5.0 software (40, 55). Differential expression was then assessed by ranked penalized t statistics using lm.series and ebayes functions in the limma package in R (http://www.bioconductor.org).

HC11 Cell Culture
HC11 cells (a kind gift from Dr. Nancy Hynes) were maintained in RPMI 1640 medium (Invitrogen) with 10% heat-inactivated fetal calf serum, 5 µg/ml insulin, and 10 ng/ml Egf (Sigma). Differentiation assays were performed by plating 1.5 x 105 cells in a six-well plate in the above medium for 3d, during which time the cells grow to confluent density, followed by incubation in media without EGF for 24 h and then treatment with 10–6 M dexamethasone (Sigma) and 5 µg/ml ovine Prl (Sigma) in media without EGF for 4 d from d 4 to d 8.

siRNA Transfection of HC11 Cells
siRNA molecules were synthesized using the Silencer siRNA Construction Kit (Ambion, Inc., Austin, TX). Two microliters of 500 nM siRNA (final concentration of 1 nM) was mixed with 200 µl serum free RPMI, 2.5 µl Lipofectamine 2000 (Invitrogen), and 200 µl OPTI-MEM media (Invitrogen) according to the Oligofectamine protocol (Invitrogen). Serum free medium (800 µl) and 200 µl of the siRNA/Lipofectamine complexes were added to each well of a six-well plate 24 h after plating the cells, and 4 h later 500 µl of RPMI/30% fetal calf serum was added to each well.


    FOOTNOTES
 
This work was supported by the National Health and Medical Research Council Australia, the New South Wales Cancer Council, the Clinical Research Center for Innovative Dairy Products and the U.S. Army Breast Cancer Research Program (BCRP) (to C.J.O.); National Institutes of Health Grant DK 61005 and Grant 10PB-0127 from the California BCRP (to A.M.W.).

Present address for M.J.N.: Developmental Biology Program, Victor Chang Cardiac Research Institute, 384 Victoria Street, Darlinghurst, New South Wales, 2010, Australia.

First Published Online February 10, 2005

1 M.J.N and S.R.O. contributed equally to this work. Back

Abbreviations: Egf, Epidermal growth factor; Gal, galanin; GFP, green fluorescent protein; PI3, phosphatidylinositol 3; P-Prl, phosphorylated Prl; Prl, prolactin; Prlr, Prl receptor; QPCR, quantitative RT-PCR; RMA, robust multiarray average; siRNA, short interfering RNA; Stat, signal transducer and activator of transcription; U-Prl, unmodified Prl; Wap, whey acidic protein.

Received for publication July 1, 2004. Accepted for publication February 2, 2005.


    REFERENCES
 TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 

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