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. 2015 Aug 12;93(3):75. doi: 10.1095/biolreprod.115.132431

Pregnancy Hyperglycemia in Prolactin Receptor Mutant, but Not Prolactin Mutant, Mice and Feeding-Responsive Regulation of Placental Lactogen Genes Implies Placental Control of Maternal Glucose Homeostasis1

Saara M Rawn 3,4, Carol Huang 5, Martha Hughes 3, Rustem Shaykhutdinov 6, Hans J Vogel 6, James C Cross 3,4,2
PMCID: PMC4710193  PMID: 26269505

Abstract

Pregnancy is often viewed as a conflict between the fetus and mother over metabolic resources. Insulin resistance occurs in mothers during pregnancy but does not normally lead to diabetes because of an increase in the number of the mother's pancreatic beta cells. In mice, this increase is dependent on prolactin (Prl) receptor signaling but the source of the ligand has been unclear. Pituitary-derived Prl is produced during the first half of pregnancy in mice but the placenta produces Prl-like hormones from implantation to term. Twenty-two separate mouse genes encode the placenta Prl-related hormones, making it challenging to assess their roles in knockout models. However, because at least four of them are thought to signal through the Prl receptor, we analyzed Prlr mutant mice and compared their phenotypes with those of Prl mutants. We found that whereas Prlr mutants develop hyperglycemia during gestation, Prl mutants do not. Serum metabolome analysis showed that Prlr mutants showed other changes consistent with diabetes. Despite the metabolic changes, fetal growth was normal in Prlr mutants. Of the four placenta-specific, Prl-related hormones that have been shown to interact with the Prlr, their gene expression localizes to different endocrine cell types. The Prl3d1 gene is expressed by trophoblast giant cells both in the labyrinth layer, sitting on the arterial side where maternal blood is highest in oxygen and nutrients, and in the junctional zone as maternal blood leaves the placenta. Expression increases during the night, though the increase in the labyrinth is circadian whereas it occurs only after feeding in the junctional zone. These data suggest that the placenta has a sophisticated endocrine system that regulates maternal glucose metabolism during pregnancy.

Keywords: diabetes, metabolism, placenta, placental lactogen, pregnancy

INTRODUCTION

Pregnancy has been described as a genetic tug of war between the fetus and mother as the fetus tries to promote its own survival and growth [1, 2]. In order to support fetal development, the mother undergoes several physiological adaptations during gestation. Red blood cell volume increases because of expansion of erythroid progenitors in the spleen [3]. In addition, cardiac output [4], lung tidal volume [5], and renal glomerular filtration rate [5] all increase, and the liver doubles in weight [6]. New olfactory interneurons are produced in the brain [7] that are thought to regulate maternal behavior [8]. There are also dramatic changes in maternal metabolism aimed at feeding the fetus. Pregnancy is a state of insulin resistance in which the mother's fat and muscle tissues require more insulin in order to shunt glucose to the fetus [4]. In order to combat insulin resistance, there is an increase in pancreatic β cells and insulin synthesis, and a lower threshold for glucose-stimulated insulin secretion [9–11]. Gestational diabetes occurs during the second trimester in humans and is associated with inadequate β-cell compensation [12, 13].

The pituitary hormones growth hormone (GH) and prolactin (Prl) are derived from a common ancestral gene, and each gene has in turn duplicated to take on new functions in the placenta [14]. There is a single GH gene in rodents and ruminants, but gene duplication has resulted in five members in humans, with expression of one restricted to the pituitary whereas the other four are expressed in the placenta [15]. The placenta-specific GH-related genes in humans are called GH-variant (GH-V), and placental lactogen (PL) A, B and L [16]. Different lines of evidence suggest that the human placenta-specific GH-related hormones regulate fetal growth and maternal metabolism during pregnancy. Mutations in the hGH-V (GH2) gene are rare, implying that it is critical [17], but pregnancies with growth-restricted babies have reduced hGH-V levels in maternal blood [18–20]. The hPLs likely promote the expansion of pancreatic β cells during normal pregnancy, based on the fact that hPL can stimulate pancreatic β-cell hyperplasia in vitro and in transgenic mice [21, 22], whereas hPL levels are reduced in gestational diabetes in some studies [23], though not all, implying that other factors besides hPL levels may play a role in β-cell proliferation. There is also evidence that Prl-like hormones can regulate appetite through interactions with leptin [24] as well as adipose tissue function [25]. Humans with deletions of both hGH-V and hPL are rare but are reported to have intrauterine growth restriction [26]. Collectively, these data indicate that placenta-specific GH/Prl-related hormones in humans regulate fetal growth and maternal metabolic adaptations to pregnancy. The hPLs and hGH-V are expressed by at least three different placental cell types (syncytiotrophoblast covering the placental villi and different extravillous cytotrophoblast subtypes) [27–29]. The details of their regulation and why there are distinct endocrine cells are unknown. Whereas it was the GH gene that duplicated in primates, it is the Prl gene that duplicated in mice [30], such that 22 placenta-specific, Prl-related genes are expressed in specific endocrine cells called trophoblast giant cells [31, 32]. What might appear to be a species difference in evolution of Prl/GH is misleading, however, because human GH binds both the GH receptor and the Prl receptor, human GH-V binds to GH receptor, and hPL-A and hPL-B bind to the Prl receptor [16].

Mouse Prl3d1 (formerly called placental lactogen I, PL-Iα) and Prl3b1 (PL-II) have been shown to bind to the Prl receptor [33], and two other close relatives, Prl3d2 (PL-Iβ) and Prl3d3 (PL-Iγ), are expected to also bind based on amino acid similarity [33]. During early pregnancy in rats and mice, pituitary Prl undergoes twice-daily surges [34]. By midgestation, Prl secretion declines and production of Prl3d1, Prl3d2, and Prl3d3 from the placenta begins, followed by the production and dominance of Prl3b1 during the second half of pregnancy [34]. Activation of the Prl receptor is important for maintenance of the corpus luteum during pregnancy, which produces relaxin and progesterone [35]. An absence of progesterone prevents blastocyst implantation [36] and, consequently, both Prl null (Prl−/−) and Prl receptor null (Prlr−/−) female mice have defective peri-implantation embryonic development. Administration of exogenous progesterone can rescue the implantation defect in Prlr−/− and Prl−/− mice [36, 37]. Prl receptor (Prlr) signaling also has an important role outside of the reproductive system. Prlr+/− mice have maladaptive responses to pregnancy, including a reduction in olfactory bulb interneuron proliferation in the brain, leading to abnormal maternal behavior [7], and a reduction in β-cell proliferation, resulting in low β-cell mass and impaired glucose tolerance [38].

Because the Prlr mediates the effects of both Prl and the PLs in mice, it is unknown whether the defects in glucose metabolism of pregnant Prlr mutant mice reflect Prl and/or PL action. It is complicated by the fact that the PLs in mice are encoded by separate genes. Our goal here was to compare Prl−/− [39] and Prlr−/− mice [40] such that phenotypic differences between pregnant Prlr−/− and Prl−/− mice should represent the actions of PLs.

MATERIALS AND METHODS

Experimental Animals

C57Bl/6 mice were obtained from Charles River Laboratories. Females were bred to males and the day that a vaginal plug was detected was designated Embryonic Day (E) 0.5. Animals were killed at 1600 or 2200 h on E16 or at 0400 or 1000 h on E17 for circadian profiling. For fasting experiments, food was removed at 2200 h on Day 16 of pregnancy for 6 or 12 h. Procedures were carried out in accordance with the Canadian Council on Animal Care and the University of Calgary Committee on Animal Care (protocol no. M09045).

Progesterone Supplementation

Prl mutant [39] and Prlr mutant [40] mice were obtained from Jackson Laboratories. To rescue the implantation defect in Prl−/− and Prlr−/− mice, 5-mg progesterone pellets with biodegradable carrier binder (Innovative Research of America) were implanted subcutaneously on E0.5, the day a vaginal plug was found, as previously described [36]. All experimental females were 5–8 wk of age when bred to wild-type males. Mice were maintained on a C57Bl/6 background.

Blood Glucose

Blood glucose was sampled from a tail vein between 0800 and 0900 h on Days 7.5, 14.5, and 17.5 of pregnancy, using an OneTouch glucose meter (LifeScan).

Blood Pressure

The noninvasive tail-cuff methodology was used to measure mean arterial blood pressure and assessed between 0830 and 1230 h on Days 6.5, 8.5, 10.5, 12.5, 14.5, and 16.5 of pregnancy [41]. Diastolic and systolic pressures were measured using the BP-2000 Blood Pressure Analysis System (Visitech Systems Incorporated). Mean blood pressures were included in the subsequent statistical analysis only if at least 10 systolic and diastolic readings were achieved for an animal on a given day of gestation.

Quantitative Real-Time PCR

Two randomly chosen placentas from each of 3 separate pregnant dams were used starting at E16. As litter size can affect serum PL levels [42, 43], only pregnant dams with litter size between eight and nine were chosen. Each placenta was dissected such that the decidua was carefully stripped away from the fetal placenta, and then the junctional zone was carefully separated from the vascular labyrinth. Junctional zone and labyrinth tissues were immediately placed in 500 μl of Trizol and stored at −80°C. Total RNA was extracted from each sample using Trizol reagent (Invitrogen). Complementary DNA was synthesized using the Quantitect Reverse Transcription Kit (Qiagen). The primer sequences used were as follows: Prl3b1, 5′-CCACACTGCTGCAATCCTTA-3′ (forward) and 5′-TGACCATGCAGACCAGAAAG-3′ (reverse); Prl2c, 5′-TGTGTGCAATGAGGAAT GGT-3′ (forward) and 5′-TAGTGTGTGAGCCTGGCTTG-3′ (reverse); PPIA, 5′-TGTCCACAGTCGGAAATGGTGA-3′ (forward) and 5′-ATTCCAGGATTCATGTGCCAG-3′ (reverse); YWHAZ, 5′-TAAATGGTCTGTCACCGTCT-3′ (forward) and 5′-GGAAATACTC GGTAGGGTGT-3′ (reverse). The primers for Pl1α/Prl3d1 (QT01052219), Prl4a1 (QT00114639), Prl8a2 (QT00157808), Prl5a1 (QT00139573), and GAPDH (QT01658692) were designed and supplied by Qiagen. The relative amount of RNA was determined by comparison with GAPDH mRNA and PPIA mRNA (for junctional zones) or YWHAZ (for labyrinth) as reference genes. GAPDH, PPIA, and YWHAZ were chosen after we tested >10 genes from Qiagen's reference gene panel, and these genes showed the least variability of all the genes tested (which included other commonly used reference genes, such as Hprt). Complementary DNA samples were labeled with Quantifast SYBR Green PCR mix (Qiagen) and the reactions performed in triplicate using the following program: 40 cycles of 95°C × 20 sec, 60°C × 20 sec, and then 72°C × 20 sec. Data were collected using the DNA Engine Opticon 2 Real-Time PCR System (MJ Research, Inc.). Ct values were determined using Opticon Monitor 2 v 2.01.10 (MJ Research, Inc.). Gene Ex Standard software (v 4.4.2.308) was used to extract qualitative data from the Ct values. One-way ANOVA and t-tests were carried out using the statistical analysis software Graphpad (Prism v 5.0c). Comparisons with P values less than 0.05 were considered statistically significant.

Serum Collection and Metabolite Extraction

Animals were anesthetized with isoflurane and whole blood was collected via cardiac puncture; serum was stored at −20°C. Serum from one animal (300 μl per sample) was filtered using a 3-kDa Nanosep microcentrifuge tube to isolate metabolites and remove contaminating proteins (VWR). Next, 130 μl of buffer containing 100 mM sodium phosphate and 2,2-dimethyl-2-silapentane-5-sulfonate to a final concentration of 0.5 mM of buffer per nuclear magnetic resonance (NMR) sample, as well as 10 μl of 1 M sodium azide, was added to each filtrate to prevent bacterial growth. Samples containing metabolites were adjusted to pH 7.0 ± 0.003. All samples were brought up to a final volume of 650 μl with deuterated water for the purposes of spectral analysis.

NMR Spectroscopy and Chemometric Analysis

We performed 1H-NMR spectroscopy on each prepared sample containing metabolites in a randomized order using a Bruker Avance 600 spectrometer (Bruker Biospin) operating at 600.22 MHz and equipped with a 5-mm TXI probe at 298 K. Spectral data were obtained in a similar method to that previously published [44]. In detail, one-dimensional 1H-NMR spectra of aqueous samples were acquired using a standard Bruker noesypr1d pulse sequence, 1D version of 2D NOESY experiment with a mixing time of 100 ms, in which the residual water was irradiated during the relaxation delay of 1.0 sec. A total of 1024 scans were collected into 65 546 data points over a spectral width of 12 195 Hz with a 90° pulse width and a 5-sec repetition time. A line broadening of 0.1 Hz was applied to the spectra prior to Fourier transformation, phasing, and baseline correction. Additional two-dimensional NMR experiments were performed for the purpose of confirming chemical shift assignments, including total correlation spectroscopy (2D 1H-13C TOCSY) and heteronuclear single quantum coherence spectroscopy (2D 1H-13C HSQC), using standard Bruker pulse programs.

Processed spectra were imported into Chenomx NMR Suite version 4.6 software for metabolite quantification using the targeted profiling approach [45]. Individual metabolite concentrations in each sample were normalized to the total sum of all metabolite concentrations in that sample to compensate for sample concentration differences. Chemometric (multivariate) statistical analysis of metabolite concentrations data was carried out on SIMCA-P software version 11.5 (Umetrics). Initially, the principal component analysis of metabolite concentration data was performed (on mean-centered data) to visualize the general structure of each data set and to identify any abnormalities (based on Hotelling T2 range) within the data set. Next, the supervised partial least-squares discriminate analysis was performed to compare the variance in metabolite concentration data scaled to unit variance among three or more maternal genotypes [46]. Orthogonal partial-least squares discriminant analysis (OPLS-DA) was performed for comparison of two groups. The quality of each model was assessed via the goodness-of prediction-parameter (Q2) and the goodness-of-fit parameter (R2).

Non-NMR-Related Statistical analysis

One-way ANOVA was performed using InStat (GraphPad Software) to determine significant differences. In order to reveal pairwise differences between means, Tukey-Kramer multiple-comparison tests were performed using GraphPad InStat.

RESULTS

Prolactin Receptor Mutant Mice Have Normally Grown Pups but Altered Serum Metabolites During Pregnancy

Before comparing the phenotypes of Prl- and Prlr-deficient mice, we wanted to expand our survey of the physiological effects of Prl receptor during pregnancy. Prlr+/− mice were initially examined to avoid any confounding effects of progesterone supplementation, which is required to maintain pregnancy in Prl−/− and Prlr−/− mice, and because physiological differences have been reported in Prlr+/− mice before [7, 38]. Consistent with previous results [38], blood glucose levels were elevated in Prlr+/− compared to wild-type mice at E 14.5 (Fig. 1A). In contrast, there was no difference in maternal cardiovascular function as assessed by mean arterial blood pressure (Fig. 1B) and spleen weight (Fig. 1C). Fetuses from Prlr+/− and wild-type mothers had similar crown-rump lengths at E10.5 (not shown) and E17.5, and similar body weight and body mass indexes at E17.5 (Fig. 2). Prlr+/− and wild-type females also had similar litter sizes of ∼8 fetuses at E17.5, and both had low numbers of resorptions near term (Fig. 2).

FIG. 1.

FIG. 1

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Maternal adaptations to pregnancy and fetal growth in Prlr+/− mutant mice. A) Fed blood glucose levels in wild-type (WT) and Prlr+/− mutant mice at E14.5 (n = 18, 13) and 17.5 (n = 19, 16). B) Mean arterial blood pressure in wild-type (n = 19) and Prlr+/− (n = 15) mutant mice. C) Maternal spleen weight in wild-type and Prlr+/− nonpregnant (n = 8, 8) and at Gestation Day 13.5 (n = 17, 16). D) Fetal crown-rump length obtained using ultrasound in wild-type (n = 17 litters) and Prlr+/− (n = 16 litters) mutant mice at E17.5. E) Average fetal weight at E17.5 in wild-type (n = 19 litters) and Prlr+/− (n = 16 litters) mutant mice. Different letter superscripts above each bar denote statistically significant differences (P < 0.05). Means that are not significantly different have the same letter.

FIG. 2.

FIG. 2

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Fetal growth, litter size, and maternal blood glucose in wild-type, Prl+/−, Prl−/− and Prlr−/− females treated with progesterone (P4). A) Crown-rump length of pups. B) Body mass index of pups. C) Number of fetuses per litter. D) Number of resorption sites per litter. E) Maternal blood glucose at E14.5, with symbols representing individual pregnant females. F) Mean blood glucose levels at different days of gestation. Prlr+/+, n = 20; Prl+/−, n = 18; Prl−/−, n = 14; Prlr+/−, n = 16; and Prlr−/−, n = 11. Different letter superscripts above each bar denote statistically significant differences (P < 0.05).

Because of the differences observed in maternal blood glucose levels, we broadened the analysis to other serum metabolites. It was first necessary to determine the metabolome profile of pregnant wild-type mice compared to nonpregnant. We looked at E17.5, a time when pancreatic β-cell mass in pregnant females is near its maximum [47] and just prior to delivery. Serum metabolite profiling revealed that lysine, alanine, threonine, formate, and proline were elevated at E17.5 in wild-type females (Fig. 3 and Supplemental Fig. S1; available online at www.biolreprod.org). The metabolic profiles of Prlr+/− and wild-type pregnant mice at E17.5 could be readily separated using multivariate statistical analysis (Supplemental Fig. S1). Pregnant Prlr+/− mice had elevated trimethylamine-N-oxide (TMAO), acetate, betaine, taurine and cholate compared to pregnant wild-type mice (Fig. 3). Pregnant Prlr+/− mice were also found to have decreased levels of glutamine, formate, glycolate, and 2-oxoisocapronate compared to wild type.

FIG. 3.

FIG. 3

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Metabolic changes observed in wild-type (n = 16) compared to Prlr+/− (n = 17) pregnant mice. Supervised OPLS-DA coefficients plot. Metabolites with negative coefficient values are higher in pregnant Prlr+/− animals, and those with positive coefficient values are higher in pregnant wild-type mice. 95% confidence intervals are shown for each metabolite.

Different Metabolic Profiles in Prlr and Prl Mutant Mice

Having established the baseline functions mediated by the Prl receptor, we determined whether any of the Prlr mutant phenotypes reflected the function of pituitary Prl from the mother. To rescue the implantation defect in Prl−/− and Prlr−/− mice, progesterone was administered. As a control, Prl+/− mice (which are similar to wild type) were also given progesterone. Fetal growth and survival were comparable between litters from Prl−/− and Prlr−/− mice supplemented with progesterone (Fig. 2), and both maternal genotypes were capable of supporting litters of up to eight fetuses (Fig. 2). Unexpectedly, though, progesterone administration impaired fetal growth and survival and altered serum metabolites in all three maternal genotypes, including the control group (Prl+/−) (Fig. 2), and so we focused on differences between Prl−/− and Prlr−/−.

The major differences between Prl−/− and Prlr−/− females were metabolic. At E14.5, Prl−/− mice had wild-type levels of blood glucose with a mean of about 8 mmol/L, whereas Prlr−/− mice had the highest blood glucose values, with the mean ∼11 mmol/L (Fig. 2) (P < 0.05). Interestingly, the diabetic phenotype of Prlr mutant mice was restricted to E14.5 (Fig. 2). At E17.5, blood glucose levels tended to remain higher in Prlr−/− mice compared to wild type but were not statistically significantly different. Profiles of other serum metabolites revealed differences between the two mutants during pregnancy. Compared to Prl−/− mice, Prlr−/− mice had markedly elevated levels of TMAO (Fig. 4), as well as citrate and histidine levels slightly closer to nonpregnant values. Although supervised orthogonal partial least squares discriminant analysis could not distinguish between the two mutants as shown in a scores scatter plot (Fig. 4), metabolite quantification confirmed that pregnant Prlr−/− mice had elevated levels of TMAO compared to pregnant Prl−/− mice (Fig. 4). No differences in acetate, betaine, taurine, cholate, or o-phosphocholine levels were found between pregnant Prl−/− and Prlr−/− mice (Fig. 4). The differences in blood glucose and TMAO levels between the pregnant Prl−/− and Prlr−/− mice imply that, although Prl and PLs use the same receptor, during pregnancy the PLs regulate glucose metabolism and Prl from the mother appears not to be essential.

FIG. 4.

FIG. 4

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Prl−/− mice do not have elevated blood glucose levels and have a different metabolic profile compared to Prlr−/− mice. A) The coefficients plot of supervised OPLS-DA of metabolomic profiles for both E17.5 Prl−/− plus progesterone versus wild-type nonpregnant and E17.5 Prlr−/− plus progesterone versus wild-type nonpregnant mice in order to visually assess differences between the two mutants. Asterisks denote metabolite concentrations that differ significantly in Prl−/− versus Prlr−/− maternal genotypes. B) Supervised OPLS-DA scores plot for all maternal genotypes analyzed. Triangles represent individual animals. R2(Y) = 0.337, Q2(Y) = 0.299, where R2(Y) is the explained variance and Q2(Y) is the predictive ability of the model. C) Quantification of selected metabolites identified in serum samples from pregnant mice at E17.5. P value on graph indicates a pairwise difference identified by Tukey-Kramer multiple comparison tests. Wild-type nonpregnant, n = 22; wild-type pregnant, n = 15; Prlr+/− pregnant, n = 16; Prl+/− plus progesterone, n = 6; Prl−/− plus progesterone, n = 13; and Prlr−/− plus progesterone, n = 10.

Gene-Specific Patterns of Placental Lactogen Expression During the Day and Within Different Zones of the Placenta

Given that one or more of the PLs from the placenta appear to regulate maternal glucose metabolism, we wanted to determine if PL expression in the placenta was regulated by nutrition in the mother. Mice are nocturnal and 75% of their daily food intake occurs during the dark cycle [48]. A subset of genes shows circadian oscillations in the liver, driven by rhythmic food intake [49]. It has been reported in the rat placenta that Prl3b1 mRNA expression shows circadian patterns that are unique to the different zones of the placenta: Prl3b1 expression in the junctional zone peaks at 0400 h, whereas in the labyrinth it peaks at 1600 h [50]. Maternal blood first enters the labyrinth zone of placenta where exchange of nutrients, waste, and gases occur between the mother and the fetus, and then departs across the junctional zone before entering into uterine veins.

We found in the mouse placenta that Prl3b1 mRNA was readily detectable in both spongiotrophoblast cells and the parietal subtype of trophoblast giant cells [31] within the junctional zone, both at 1600 h on E16 and 12 h later at 0400 h early on E17, with no obvious differences in cell-type-specific expression between these two time points (Fig. 5). Using quantitative real-time PCR, we found that Prl3b1 expression levels did not change significantly throughout the day in either the junctional zone or the labyrinth in mice, unlike what had been reported in rats (Fig. 5). As a control, we noted that melatonin receptor 1 alpha (MelR1a) mRNA changed during the course of the day (Fig. 5), similar to what was reported in the rat placenta [50].

FIG. 5.

FIG. 5

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Expression of Prl3b1 mRNA in the mouse placenta. A) Prl3b1 and melatonin receptor 1 alpha expression (MelR1a) in the junctional zone and labyrinth of the placenta at 6-h intervals starting on E16. Blue bars indicate the dark cycle when mice are actively feeding. Median values with standard error of the mean are shown. Different letter superscripts above each bar denote statistically significant differences (P < 0.05). RNA from six placentas (two placentas from three pregnant mice) was analyzed at each time point. B) In situ hybridization showing Prl3b1 gene expression in blue in placental cells at 1600 h on E16 and at 0400 h on E17. P-TGC, parietal trophoblast giant cells; C-TGC, canal trophoblast giant cells; SpT, spongiotrophoblast. Red arrowheads indicate the nuclei of parietal trophoblast giant cells. Original magnification ×2 (left panels) and ×200 (all other panels).

We then looked at expression of the other mouse PLs (Prl3d1, Prl3d2, and Prl3d3). Though expression of Prl3d genes falls off dramatically after midgestation [30, 32], we readily detected their expression by quantitative real-time PCR at E16/17. Prl3d1 expression in the placenta increased overnight. In the junctional zone, Prl3d1 expression began to increase at 0400 h, and by 1000 h was significantly higher than at 1600 h on the previous day (Fig. 6). Prl3d1 gene expression pattern in the labyrinth was different from that observed in the junctional zone, as mRNA levels peaked at 0400 h and remained elevated at 1000 h. In contrast to Prl3d1, Prl3d2 expression showed no change in the junctional zone but increased to peak at 0400 h in the labyrinth (Fig. 6). Prl3d3 expression was different as it was consistent throughout the 24-h time period in both the junctional zone and the labyrinth of the placenta (Fig. 6).

FIG. 6.

FIG. 6

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Expression of Prl3d1, Prl3d2, and Prl3d3 mRNA in the junctional zone and labyrinth of the placenta at 6-h intervals starting on E16. RNA from six placentas (two placentas from three pregnant mice) was analyzed at each time point. Different letter superscripts above each bar denote statistically significant differences (P < 0.05).

Maternal Nutritional Changes Influence Placental Lactogen Gene Expression

Our observations with Prl3d1 and Prl3d2 lead us to hypothesize that they are regulated by maternal food intake, presumably responding to levels of nutrients and/or other metabolic hormones. To test this, mice were fasted beginning at 2200 h on Day 16 of pregnancy, and placentas were harvested 6 or 12 h later to measure PL mRNA expression levels. The pregnant mice lost up to 2.1% of their body weight during the fasting period. No significant change in Prl3d1 expression was observed in the labyrinth after either 6 or 10 h of fasting. However, Prl3d1 mRNA expression in the junctional zone failed to show the normal late-night increase (Fig. 7) and levels were significantly lower than in wild type (P < 0.05). When we examined Prl3d2, we found an increase in its expression in the junctional zone but not the labyrinth after 6 h of fasting (Fig. 7A). Prl3d3 expression level in the placenta was not affected by fasting. Although Prl3b1 protein (PL-II) levels have been reported to increase in the serum after fasting in mice [51], fasting had no effect on Prl3b1 mRNA levels (Fig. 7A).

FIG. 7.

FIG. 7

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Effect of nutrition on expression of placental Prl-related hormone mRNAs. A) Effects of overnight fasting on Prl3d1, Prl3d2, Prl3d3, and Prl3b1 transcript levels in the labyrinth and junctional zone of the murine placenta. B) Cartoon showing structure of the mature mouse placenta and location of the different endocrine cells. C) Summary of expression patterns of PL genes in the mouse placenta and their responsiveness to maternal metabolic status based on published microarray data sets from Chen et al. [52], Schulz et al. [54], and Baisden et al. [53].

Our results indicated that Prl3d1 and Prl3d2 expression is responsive to acute changes in dietary intake. To determine whether Prl-related gene expression changed in response to other types of metabolic changes, we analyzed data sets from published microarray studies (http://www.ncbi.nlm.nih.gov/geo/) that had examined gene expression in the mouse placenta (Fig. 7C). The studies included 50% restriction in total dietary intake [52] and dexamethasone treatment [53] in pregnant mice, analyzing the placenta at term, and treatment of cultured mouse trophoblast giant cells with the metabolic hormone leptin [54]. Feed restriction resulted in significant (P < 0.05) reductions in Prl3d1, Prl3d2, and Prl3d3 mRNA but did not alter expression of Prl3b1. Interestingly, the expression of Prl3a1 and Prl3c1 genes was also reduced. Although these two genes are closely related and within the same evolutionary clade as the better-known Prl3b1 and Prl3d1/2/3 [14], their functions and receptor binding activities have not been reported. Notably, restriction in total dietary intake during the first half of gestation does not significantly alter expression of the Prl3 subclass of Prl-related hormone genes, at least when the placenta is analyzed at E11.5 [55]. Treatment of mice with dexamethasone results in reduced Prl3d1 and Prl3d2 gene expression, but increased Prl3a1 [53]. Leptin treatment of trophoblast giant cells in culture results in increased Prl3d1, Prl3d2, and Prl3d3 [54].

DISCUSSION

Prl receptor signaling plays important roles in maternal adaptations to pregnancy, including corpus luteum maintenance, mammary gland development, olfactory bulb interneuron proliferation in the brain, maternal behavior, and expansion of pancreatic β cells [7, 38, 56]. Although the PLs are thought to be the primary agonists of the Prl receptor after midgestation based on expression patterns, the relative contributions of Prl from the maternal pituitary and PLs from the placenta had not been demonstrated. In addition, previous reports had not determined whether the Prl receptor mediated any other maternal adaptations to pregnancy and its contribution to fetal growth. Our results rule out roles for maternal pituitary Prl in any of the maternal adaptations to pregnancy assessed in this study and demonstrate that Prlr signaling is not required for fetal growth and survival. These results indicate that the previously reported role of Prlr in promotion of maternal pancreatic β-cell proliferation [38] is its major metabolic effect during pregnancy.

In vitro studies have previously demonstrated that PLs can stimulate insulin secretion and pancreatic β-cell proliferation [57–59]. Overexpression of mouse PLs in pancreatic β cells induces pancreatic β-cell proliferation, increases plasma insulin concentrations, and causes hypoglycemia [60]. Conversely, we previously reported that Prlr+/− mice have elevated blood glucose levels and lower insulin as well as reduced β-cell mass during pregnancy [38]. We report here for the first time that pituitary Prl does not modulate maternal glucose homeostasis during pregnancy, based on the observation that Prl−/− mice have normal blood glucose levels whereas Prlr−/− mice have even higher blood glucose levels than Prlr+/− mice during pregnancy compared to wild type. We did not examine insulin levels or β-cell mass in the Prl mutants as there was no indication given their normal glucose levels. This implies that the PLs are the normal ligands for the Prlr that drive pancreatic β-cell expansion.

We compared serum metabolite profiles between Prlr+/− and wild-type mice and between the Prl−/− and Prlr−/− mice, and observed significant differences in both cases. The osmolyte TMAO emerged as the only metabolite that was elevated in both the Prlr+/− and the Prlr−/− mice. This was of interest because dysregulation in TMAO levels has been reported in other diabetes models. For example, metabolomic analysis carried out on hepatic tissue of db/db mice, a model for type 2 diabetes mellitus, found lower levels of TMAO compared to nondiabetic mice [61]. TMAO is elevated in the urine of db/db mice, diabetic fa/fa rats, and humans with type 2 diabetes [62, 63], and it is also elevated in the plasma of mice that have been fed a high-fat diet [64]. A study carried out in patients with type 2 diabetes found that diabetic patients excreted higher levels of TMAO in urine compared to nondiabetic individuals, even in the presence of good metabolic control [65]. TMAO is an osmolyte that is synthesized in the medullar cells of the kidney [65]. It normally functions to reduce protein perturbations when there are high levels of urea, but it may also function in diabetes to counteract the hyperosmotic effects of glucose in the renal system. In addition, it may be a marker of renal dysfunction [65]. Other metabolites that were found to be elevated in the serum of pregnant Prlr+/− though not Prlr−/− mice included acetate, betaine, cholate, o-phosphocholine, and taurine. Both acetate and the osmolyte betaine have been found to be elevated in urine of type II diabetics [65]. Similar to TMAO, excessive betaine excretion in the urine may be the by-product of excessive production of sorbitol secondary to chronic hyperglycemia, and glycation of the betaine transport system as well as hyperglycemia-induced renal tubular dysfunction can cause elevated betaine excretion in the urine.

The up-regulation of taurine in the mutants is interesting, and it may be an adaptive mechanism to the reduced Prl receptor signaling. Taurine is a sulfur-containing amino acid. Its level is often found to be decreased in diabetes and it has been proposed as a therapeutic agent to treat diabetes-related complication [66]. Taurine has been found to be an effective modulator of many diabetic complications via its multiple biological actions including antioxidation, osmoregulation, and bile acid conjugation [66]. For example, taurine has been found to protect pancreatic islets from reactive oxygen species by suppressing the effects of oleate [67]. Taurine has also been shown to modify fetal programming of the pancreas, as taurine supplementation during pregnancy reverses some of the negative effects of maternal malnutrition during pregnancy on the β-cell mass of offspring [68]. Furthermore, taurine can stimulate insulin release from β cells in culture [69], and, as such, elevated levels of taurine towards the end of the pregnancy may explain in part the near-normal glucose levels of Prlr mutant mice on Day 17 of pregnancy. It is important to point out that these metabolic profiles were generated near term, when Prlr+/− and wild-type mice had similar blood glucose levels. Therefore, the changes in metabolite profiles are not likely to be secondary to hyperglycemia, but rather to result from a distinct effect of Prl and PLs on metabolism.

Given that PLs enhance β-cell proliferation as well as insulin synthesis and secretion during rodent pregnancy [70], and that Prl3b1 is the predominant PL expressed in late gestation by the placenta, we hypothesized that maternal feeding would affect Prl3b1 gene expression, with higher levels of Prl3b1 during feeding when higher insulin levels are required to maintain maternal glucose homeostasis. However, in contrast to studies in rats, where Prl3b1 expression has a circadian pattern, we found that on Days 16–17 of pregnancy, Prl3b1 mRNA expression in mice placenta did not have a circadian pattern, and fasting had no impact on Prl3b1 mRNA expression. Although our results did not support the rat studies, a study in Swiss Webster mice found that fasting during early pregnancy elicited an increase in maternal serum levels of Prl3b1 hormone after 24 h on Day 12 of gestation [51]. Elevated levels of circulating Prl3b1 hormone after fasting could arise via mechanisms other than increasing transcription. For example, the hormone could undergo posttranslational modifications to increase its half-life in the blood [71], or the amount of hormone could be controlled at the translational or secretion levels [72]. It is also possible that the difference in the stage of pregnancy (Day 12 in the previous study and Day 16–17 in the present study) accounts for the different observations. It is interesting to note that Prl3b1 mRNA expression levels may also differ because of differences in mouse strain, as depending on the genetic background of the sire, placentas from heterotopic breeding are significantly larger and produce higher levels of PLs than placentas derived from within-strain breeding [43].

In contrast to the unvarying expression pattern of Prl3b1, Prl3d1 mRNA expression in the placenta was elevated late during the dark cycle, though this failed to occur if the pregnant females were fasted. Because mouse Prl3d1 expression levels peak at midpregnancy and are considerably lower in the second half of gestation [32], it was unexpected to detect Prl3d mRNA in both the junctional zone and the labyrinth on Days 16–17 of pregnancy and in a manner that is responsive to nutritional status. In future studies, it will be important to determine whether serum levels of Prl3d also increase in response to maternal nutrient intake, when isoform-specific antibodies that allows us to distinguish between Prl3d isoforms become available.

The difference in expression pattern of Prl3d1 and Prl3d2 in the labyrinth versus the junctional zone was unexpected. The reason for an earlier increase in Prl3d1 mRNA levels in the labyrinth may be a result of a difference in exposure to nutrient-rich blood in the various placental functional zones. Furthermore, factors produced in different locations within the placenta may have different targets. For example, feed-responsive Prl3d1 production from the parietal trophoblast giant cells in the junctional zone would target mainly the maternal blood supply given their proximity to maternal venous blood as it leaves the placenta, whereas fasting-responsive Prl3d2 produced in the labyrinth could target the fetus as well, because maternal-fetal exchange occurs in this placental layer. After eating, the nutrient-rich blood from the mother would reach the labyrinth first before it reaches the parietal trophoblast giant cells in the junctional zone, given their physical location [73]. In response to the high nutrient and glucose load, Prl3d transcript levels would increase in the labyrinth, potentially via induction by ETS transcription factors [74–76]. Because glucose transporters in the placental labyrinth are likely to remove glucose from the maternal circulation to meet fetal demand [77], the delay in the rise of Prl3d1 mRNA expression in the parietal trophoblast giant cells could reflect exposure to blood with lower nutrient and glucose content in comparison to the labyrinth.

In conclusion, this study provides the first evidence that pituitary Prl from the mother is not essential for regulation of normal glucose levels during pregnancy and suggests that it is the PLs that promote the expansion of pancreatic β cells in the mother's pancreas through the Prl receptor and prevent her from developing gestational diabetes. Prl3d1 and Prl3d2 genes in the placenta are in turn responsive to maternal nutrient status during pregnancy. In the postprandial state, when more insulin synthesis and secretion is required, a rising PL level in the mother can further increase serum insulin levels, which would benefit the maternal metabolic status.

ACKNOWLEDGMENT

The authors thank David Natale and Xiang Zhao for helpful discussions, and Fran Snider for technical assistance.

Footnotes

1

Supported by a grant from the Canadian Institutes of Health Research to J.C.C. (MOP-37776).

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