Abstract
The placenta secretes a prolactin (PRL)-like hormone PRL3B1 (placental lactogen II), a luteotropic hormone essential for maintaining pregnancy until labor in mice. A report from 1984 examined the secretion pattern of PRL3B1 in prepartum mice. In the current study, we found contradictory findings in the secretion pattern that invalidate the previous report. By measuring maternal plasma PRL3B1 and PRL every 4 hrs from gestational day 17 (G17), we newly discovered that maternal plasma PRL3B1 levels decrease rapidly in prepartum C57BL/6 mice. Interestingly, the onset of this decline coincided with the PRL surge at G18, demonstrating a plasma prolactin axis shift from placental to pituitary origin. We also found that maternal plasma progesterone regression precedes the onset of the PRL shift. The level of Prl3b1 mRNA was determined by RT-qPCR in the placenta and remained stable until parturition, implying that PRL3B1 peptide production or secretion was suppressed. We hypothesized that production of the PRL family, the 25 paralogous PRL proteins exclusively expressed in mice placenta, would decrease alongside PRL3B1 during this period. To investigate this hypothesis and to seek proteomic changes, we performed a shotgun proteome analysis of the placental tissue using data-independent acquisition mass spectrometry (DIA-MS). Up to 5,891 proteins were identified, including 17 PRL family members. Relative quantitative analysis between embryonic day 17 (E17) and E18 placentas showed no significant difference in the expression of PRL3B1 and most PRL family members except PRL7C1. These results suggest that PRL3B1 secretion from the placenta is suppressed at G18 (E18).
THE PLACENTA is an endocrine organ that maintains pregnancy by synthesizing and secreting a wide range of hormones identical or analogous to those produced by the hypothalamus, pituitary gland, ovaries, and adrenal glands [1]. A hallmark example in mice is pituitary hormone prolactin (PRL) and its paralog PRL family proteins; 25 PRL family-like genes identified in trophoblast cells and secreted by the placenta [2-4]. The PRL family is multifunctional, ranging from initiation of pregnancy to postpartum adaptations [3, 5]. The pituitary gland secretes PRL in a pulsive manner in post-coital female mice [6], initiating the first step of pregnancy. PRL stimulates the corpus luteum to induce progesterone (P4) secretion [7, 8], and in turn, P4 supports embryo implantation, decidualization, and pregnancy maintenance [8]. A newly formed placenta secretes PRL-like hormones, PRL family 3, subfamily D, member 1 (PRL3D1: placental lactogen I (PL-I)) and PRL family 3, subfamily B, member 1 (PRL3B1: placental lactogen II (PL-II)) [3, 9]. In mice, PRL3D1 and PRL3B1 appear in the maternal circulation from gestational day 9 (G9). While PRL3D1 becomes undetectable at G11, PRL3B1 remains high from mid-pregnancy until term [10, 11]. Since PRL3D1 and PRL3B1 bind to the prolactin receptor (PRLR) and activate signal transduction [12], their biological functions are thought to be analogous to PRL [13]. High levels of PRL3D1 and PRL3B1 suppress pituitary PRL secretion [5], and it is considered that from mid-pregnancy, the hypothalamus-pituitary-gonadal axis with PRL is replaced by the placenta-gonadal axis with PRL3B1 [3]. During this time, all other PRL family members are independently expressed at the feto-maternal interface, acting as local autocrine/paracrine cytokines to stabilize and promote conceptus development [14-18].
Towards the end of pregnancy, the hypothalamus-pituitary axis escapes suppression, and PRL surges on G18 [11, 19]. Elevated PRL signals trigger nurturing behavior in the mother [20, 21]. Although PRL and PRL3B1 are critical for physiological transitions into motherhood and fetal development [22-24], knowledge of mouse PRL hormones during late pregnancy is severely lacking. Only one study reported maternal PRL3B1 concentrations, which were considered high until placenta detachment from the uterus [11]. However, a single study is likely not sufficient to clarify the secretory and expression profile of the PRL family.
In the present study, we evaluated the prepartum PRL family expression patterns to further understand the possible role of PRL family proteins at the end of pregnancy. For this purpose, we reevaluated the secretion patterns of prepartum PRL3B1 and PRL and measured plasma P4 concentrations to see how it relates to PRL3B1 and PRL levels. To investigate whether the PRL3B1 decline occurs at the mRNA level in the placenta, we also examined the Prl3b1 mRNA level with quantitative reverse transcription polymerase chain reaction (RT-qPCR).
Furthermore, we performed a shotgun proteomic analysis of the placenta using data-independent acquisition mass spectrometry (DIA-MS) [25, 26] to examine the production of PRL3B1 and the other 24 paralogous PRL proteins expressed in mice placenta. A total of 17 PRL family members were identified, and relative quantitative analysis revealed the differences in protein levels between embryonic day 17 (E17) and E18 placentas.
Materials and Methods
Animals
The animal experimentation protocol was approved by the Animal Care and Experimentation Committee, Gunma University Showa Campus. C57BL/6J (C57BL/6JJcl) mice were obtained from Japan SLC Inc. (Shizuoka, Japan). The mice were kept at 24°C under a 12-hr light/dark cycle (lights on, 7:00 to 19:00) and 55% relative humidity with ad libitum access to water and standard rat chow (MF; Oriental Yeast Co., Ltd., Tokyo, Japan). The four stages of the estrous cycle: proestrus, estrus, metestrus, and diestrus, were identified by observing the vagina twice a day at 8:00 and 18:00. Mice that showed a wide vaginal opening with swollen, moist, pink vaginal tissue were considered proestrus or estrus [27]. At proestrus or estrus, 12–20 weeks of age virgin mice were mated by adding males at 18:00. Males were removed at 8:00 the following day, and females with vaginal plugs were defined as gestational day 0 (G0), while conceptuses were defined as embryonic day 0 (E0). After fertilization, dams were placed in separate plastic cages. The expected timing of parturition with this method was between G19 1:00 to 10:00. Dark phase procedures were performed under a red light (20W). Mice in the diestrus phase of the estrous cycle at 12:00 were used as negative controls due to hormonal stability (e.g., PRL, PRL3B1, and P4) [28, 29].
Measurement of plasma PRL3B1, PRL, and P4 levels
Pregnant mice were sacrificed every four hrs, from G17 12:00 through G19 0:00 by decapitation. Trunk blood was collected in ice-cold conical tubes treated with Heparin sodium (Mochida Pharmaceutical Co., Ltd., Tokyo, Japan). Blood samples were spun down at 10,000 rpm for 8 mins at 4°C. Plasma samples were collected and stored at –80°C until assay. The number of samples assayed from each time point is described in the figures (n = 4–12/time points). PRL3B1, PRL, and P4 levels in the maternal plasma were measured using commercially available enzyme-linked immunosorbent assay (ELISA) kits for PRL3B1 (MBS7606017, Lot No. M1597F107, M1597G026 and M1597G055; MyBioSource, San Diego, CA, USA), for PRL (ab100736, Lot No. GR3403414-1 and GR3302329-1; Abcam, Cambridge, UK), and for P4 (ADI-900-011, Lot No. 08182008C; Enzo Life Science Inc., Farmingdale, NY, USA), respectively. A standard curve was included with each assay, and absorbance was measured at 450 nm for PRL3B1 and PRL and at 405 nm for P4 by a Versamax microplate reader (Molecular Devices, San Jose, CA, USA). The lowest detection limits for PRL3B1, PRL, and P4 assays were 150 pg/mL, 30 pg/mL, and 8.57 pg/mL, respectively. Measurements were performed in duplicate. The number of conceptus was counted, and pregnant females with 6 to 10 conceptuses were used in this study to minimize the variation in PRL3B1 levels [30].
Placenta tissue sampling
Placenta samples were collected every four hrs from E18 8:00 through E19 0:00 for RT-qPCR. Placenta samples from E17 20:00 and E18 20:00 were collected for placental proteomics analysis. Immediately after pregnant dams were sacrificed for blood samples, the uterus was removed by a caesarian section and dropped into ice-cold phosphate-buffered saline (PBS). The uterus and amnion were cut open by scissors, and the sex of the fetus was determined by examining the external genitalia and pigment spots on the scrotum [31]. Only placentas from female fetuses were chosen for sampling since sex differentiation of gene expression in the placenta has been reported [32]. Each placenta was carefully removed from the uterus. The umbilical cord, yolk sac, and chorionic plate were cut off close to their insertion sites with micro-surgery scissors [33]. Placentas were washed in clean ice-cold PBS (–) (Fujifilm Wako Pure Chemical Industry Co., Ltd., Tokyo, Japan) three times, snap-frozen in liquid nitrogen, and stored at –80°C until assay. Placenta samples for proteomics analysis were collected from individual dams and weighted by a NewClassic MS-L electronic scale (Mettler-Toledo International Inc., Greifensee, Switzerland). Because the PRL family proteins are spatially and temporarily produced in different cells of the placenta: decidual cells, trophoblast giant cells (TGCs), spongiotrophoblast cells, labyrinth trophoblasts, and endovascular trophoblasts [15, 18], the whole placenta was collected. According to a previous study, Prl3b1 mRNA is exclusively produced in parietal TGSs, canal TGCs, and sinusoidal TGCs [15], suggesting that PRL3B1 production is confined to placenta samples [15, 34]. The whole placenta was chosen for the DIA-MS to measure all the PRL family content in the placenta simultaneously. This sampling method was also adopted to standardize the quality of placenta samples by avoiding hemorrhage, placental damage, and other procedure effects that may negatively impact the proteomic profile.
RT-qPCR
Placenta samples from each group (n = 4/time points) were cut into 20 μg quarter circle shapes with clean scalpels (Feather Safety Razor Co., Ltd., Tokyo, Japan). Total RNA was extracted from four placenta samples per time point using RNeasy mini kit (Qiagen, Hilden, Germany) and treated with DNase I (Qiagen). Total RNA (2 μg) was reverse transcribed into cDNA using a High-Capacity RNA-to-DNA Kit (Applied Biosystems, Foster City, CA). The synthesized cDNA was subjected to quantitative RT-PCR using an ABI StepOne Real-Time PCR platform (Applied Biosystems) with TaqMan probes (Thermo Fisher Scientific, Waltham, MA, USA) specific for mice Prl3b1 (Mm00435852_m1). The mRNA level was normalized by comparison with the mouse glyceraldehyde 3-phosphate dehydrogenase (Gapdh Mm99999915_g1) mRNA levels. The RT-qPCR protocol was as follows: 95°C for 20 secs, 40 amplification cycles by 95°C for 1 sec, and 60°C for 20 secs.
Sample preparation for LC-MS/MS
Proteome samples (n = 3/time points) were prepared as described in a previous study [25]. In brief, the samples were dissolved in 100 mM Tris-HCl (pH 8.0) containing 4% sodium dodecyl sulfate using a water bath-type sonicator (SONIC BIO Co., Kanagawa, Japan). Extracted proteins were quantified using Pierce™ BCA Protein Assay Kit (Thermo Fisher Scientific) at 500 ng/μL. Protein extracts were reduced with 20 mM tris (2-carboxyethyl) phosphine for 10 min at 80°C, followed by alkylation with 30 mM iodoacetamide for 30 min at room temperature in the dark. Protein purification and digestion were performed using SP3 method [25, 35]. Tryptic digestion was performed using 500 ng/μL Trypsin/Lys-C Mix (Promega, Madison, WI, USA) overnight at 37°C. The digests were purified using GL-Tip SDB (GL Sciences, Tokyo, Japan) according to the manufacturer’s protocol. Peptides were dissolved again in 2% ACN containing 0.1% TFA and quantified using BCA assay at 200 ng/μL.
DIA-MS-Based proteomics
The shotgun proteome analysis was performed as previously reported with a few modifications [26, 36]. Peptides were directly injected onto a 75 μm × 12 cm nano-capillary column (Nikkyo Technos) at 40°C and then separated with a 40 min gradient at a flow rate of 200 nL/min using an UltiMate 3000 RSLCnano LC system (Thermo Fisher Scientific). Peptides eluting from the column were analyzed on a Q Exactive HF-X (Thermo Fisher Scientific) for overlapping window DIA-MS. MS1 spectra were collected in the range of 495–785 m/z at 30,000 resolution to set an automatic gain control (AGC) target of 3e6 and maximum injection time of “auto.” MS2 spectra were collected in the range of more than 200 m/z at 15,000 resolution to set an AGC target of 3e6, maximum injection time of “auto,” and normalized collision energy of 28. An isolation width for MS2 was set to 4 m/z, and overlapping window patterns in 500–780 m/z were used for window placements optimized by Scaffold DIA (Proteome Software, Inc., Portland, OR, USA).
MS files were searched against human spectral library using Scaffold DIA. The human spectral library was generated from human protein sequence database (UniProt id UP000005640, reviewed, canonical; 20,431 entries) by Prosit [37]. Scaffold DIA search parameters were as follows: experimental data search enzyme, trypsin; maximum missed cleavage sites, 1; precursor mass tolerance, 10 ppm; fragment mass tolerance, 10 ppm; static modification, cysteine carbamidomethylation. Protein identification threshold was set at less than 1% for both peptide and protein false discovery rates (FDR). Peptide quantification was calculated using the EncyclopeDIA algorithm [38] in Scaffold DIA. The four highest-quality fragment ions were selected for quantitation for each peptide. Protein quantification was estimated from the summed peptide quantification.
The software Perseus (v2.0.11; https://maxquant.net/perseus/) was used for comparative placenta proteomic analysis [39]. Quantitative protein data were log2 transformed (protein intensities) and filtered so that for each protein, at least one group contained a minimum of 70% valid values. Remaining missing values were imputed with a randomized value drawn from a normal distribution provided by Perseus. Each group’s mean protein intensities and intensity-based absolute quantification (iBAQ) were calculated with standard error (SE). Differentially expressed proteins (DEPs) between the E17 20:00 and E18 20:00 groups were defined by a ≥2-fold change and significant at probability values of p < 0.05 (Welch’s t-test). Hydroxysteroid 11-beta dehydrogenase 2 (HSD11B2) was used as a positive control for the DIA-MS due to its consistent decrease in prepartum mouse placenta [40, 41]. The Z-score of PRL family proteins and DEPs was calculated to create a heatmap. Hierarchical clustering analysis was performed on the DEPs.
Gene ontology (GO) analysis on the DEPs was performed by Database for Annotation, Visualization, and Integrated Discovery (DAVID v2023q1; https://david.ncifcrf.gov/) [42, 43].
Statistical analysis
Statistical analyses and graph creation were performed using GraphPad Prism (v10.0.2) (GraphPad Software, San Diego, CA, USA) and Perseus (v2.0.11; https://maxquant.net/perseus/). Plasma PRL3B1, PRL, and P4 data were analyzed by one-way Analysis of variance (ANOVA) followed by Tukey-Kramer’s multiple comparison test. RT-qPCR data were analyzed by one-way ANOVA. Welch’s t-test was applied for the relative quantitative analysis between E17 20:00 and E18 20:00 MS results. Fisher’s exact test was applied for GO enrichment analysis performed by DAVID. Placenta weight data were analyzed by Student’s t-test. A p-value of <0.05 was considered statistically significant for all analyses.
Results
Marked changes in maternal plasma PRL3B1, PRL, and progesterone (P4) concentrations during late pregnancy
The litter size of the dams was 6 pups (8%), 7 pups (26%), 8 pups (35%), 9 pups (27%), and 10 pups (4%). Changes in PRL3B1 plasma concentration from G17 20:00 to G19 0:00 are shown (n = 5–11/time points) (Fig. 1A). One-way ANOVA revealed a statistically significant difference in mean exam score among the groups (F = 35.24, p < 0.0001). PRL3B1 concentration was at a plateau until G18 4:00. Though there was individual divergence, PRL3B1 levels began to decrease from G18 8:00. There was a significant decline of plasma PRL3B1 concentration during the light phase between G18 8:00 and G18 12:00 before reaching complete regression at G18 20:00 (Tukey-Kramer’s test, p < 0.0001).
Changes in the plasma concentration of PRL from G17 20:00 to G19 0:00 are shown (n = 5–12/time points) (Fig. 1B). One-way ANOVA revealed a statistically significant difference in mean exam score between groups (F = 8.836, p < 0.0001). Contrary to PRL3B1, PRL secretion significantly increased between G18 8:00 and G18 12:00 (Tukey-Kramer’s test, p < 0.005). The onset of PRL3B1 regression and the prepartum PRL surge simultaneously occurred between G18 8:00 and G18 12:00 (Fig. 1A and 1B).
Changes in P4 plasma concentration from G17 12:00 to G18 20:00 are shown (n = 4/time points) (Fig. 2). One-way ANOVA revealed a statistically significant difference in mean exam score among the groups (F = 8.722, p < 0.0001). P4 concentration gradually decreased from G17 12:00 until G18 20:00, except for a slight increase detected at G18 4:00. There was a significant decline of plasma P4 concentration from G17 20:00 (Tukey-Kramer’s test, p < 0.05).
Stable Prl3b1 mRNA levels in the placenta during late pregnancy
The Prl3b1 mRNA levels in the placenta from E18 4:00 to E19 0:00 are shown (n = 4/time points) (Fig. 3). Contrary to the sharp decrease in the concentration of PRL3B1 (Fig. 1A), no significant changes were seen in mRNA levels between these time points (one-way ANOVA, F = 1.895, p = 0.1453).
This disassociation between the plasma protein and placental mRNA level motivated us to perform a proteome analysis on the placenta. Since the half-life of circulating mouse PRL3B1 is extremely short, less than 20 secs during the rapid phase of the bi-exponential decay [44], we speculated that there must be a biological process in the placenta that regulates PRL3B1 secretion. We hypothesized that the function and the protein synthesis of the placenta declined between E17 20:00 and E18 20:00 when it stopped secreting PRL3B1 (Fig. 1A). Thus, we thought we could detect the reduction of PRL3B1 and the PRL family protein contents, and a shift in the proteomic profile by LC-MS/MS.
E17 20:00 and E18 20:00 placental proteomic profiles and the analysis
Placenta weights from E17 and E18 were 96 ± 3 mg and 93 ± 3 mg (mean ± SE, n = 12), respectively (Fig. S1). No statistical significance was observed between the two groups. Placenta weights were used to normalize the MS results. Three E17 20:00 and E18 20:00 placenta samples were subjected to DIA-MS, resulting in 5,891 identified proteins (Supplementary data: Table S1). Results of the MS are shown as a volcano plot (Fig. 4). Among the proteins, 20 PRL family members were detected, and at least 17 members were identified (Table 1). The names of the proteins are described with standardized nomenclature for the mouse PRL family, but their official aliases are written together [9]. Relative expression of the PRL family proteins from each sample is shown as a heatmap (Fig. 5). Peptides were indistinguishable between PRL2C2 and PRL2C3, and between PRL3D1, PRL3D2 and PRL3D3 [4,15], and thus were grouped as identical proteins (Table 1 and Fig. 5). Relative quantitative analysis between the two placenta groups resulted in PRL7C1 being the only PRL family member markedly upregulated in E18 samples (Table 1). Contrary to our hypothesis, there were no significant changes in PRL3B1 expression (Table 1).
Table 1
Identified PRL family proteins and relative quantitative analysis between embryonic day (E17) and E18 placentas
| UniProta |
Gene symbol |
Description |
Official alias symbol |
Peptide count |
Unique peptides |
Mean iBAQb ± SE
E17 20:00 |
Mean iBAQb ± SE
E18 20:00 |
p-valuec |
| Q9DAS4 |
PRL8A8 |
Prolactin-8A8 |
PLP-Cγ |
8 |
7 |
8.3 ± 7.4 |
8.2 ± 7.3 |
ns |
| Q9DAZ2 |
PRL2B1 |
Prolactin-2B1 |
PLP-K |
7 |
7 |
8.3 ± 7.4 |
8.3 ± 7.5 |
ns |
| O54832 |
PRL8A2 |
Decidual PRL-related protein |
DPRP |
7 |
7 |
8.4 ± 7.5 |
8.5 ± 7.7 |
ns |
| Q9JLV9 |
PRL2C5 |
Prolactin-2C5 |
PLF4 |
6 |
4 |
7.9 ± 7.0 |
8.0 ± 6.7 |
ns |
| P09586 |
PRL3B1 |
Prolactin-3B1 |
PL-II |
5 |
5 |
8.8 ± 8.0 |
8.8 ± 7.5 |
ns |
| O54831 |
PRL7A2 |
Prolactin-7A2 |
PLP-F |
5 |
5 |
7.9 ± 7.0 |
7.7 ± 6.6 |
ns |
| Q9JHK0 |
PRL2A1 |
Prolactin-2A1 |
PLP-M |
5 |
5 |
7.5 ± 6.7 |
7.6 ± 6.4 |
ns |
| P04095 |
PRL2C2 |
Prolactin-2C2 |
PLF-1 |
5 |
3 |
7.2 ± 6.6 |
7.3 ± 6.0 |
ns |
| ⇔P04768 |
PRL2C3 |
Prolactin-2C3 |
PLF-2 |
5 |
3 |
7.2 ± 6.6 |
7.3 ±6.0 |
ns |
| P04769 |
PRL7D1 |
Prolactin-7D1 |
PLF-RP, PRP |
5 |
5 |
7.5 ± 6.8 |
7.5 ± 6.3 |
ns |
| Q78Y73 |
PRL3A1 |
Growth hormone d9 |
PLP-I |
4 |
4 |
8.0 ± 7.4 |
7.8 ± 7.0 |
ns |
| Q8CGZ9 |
PRL7B1 |
Prolactin-7B1 |
PLP-N |
4 |
4 |
6.5 ± 6.0 |
6.5 ± 5.7 |
ns |
| O54830 |
PRL7A1 |
Prolactin-7A1 |
PLP-E |
4 |
4 |
7.0 ± 6.6 |
7.2 ± 6.4 |
ns |
| Q9DAY2 |
PRL8C6 |
Prolactin-8C6 |
PLP-Cα |
3 |
2 |
7.5 ± 7.0 |
7.6 ± 6.9 |
ns |
| Q9CQ58 |
PRL8A9 |
Prolactin-8A9 |
PLP-Cβ |
3 |
2 |
8.5 ± 7.9 |
8.5 ± 7.7 |
ns |
| P18121 |
PRL3D1 |
Prolactin-3D1 |
PL-Iα |
2 |
2 |
6.2 ± 5.7 |
6.2 ± 5.9 |
ns |
| ⇔A0A0M6L0J6 |
PRL3D2 |
Growth hormone d5 |
PL-Iβ |
2 |
2 |
6.2 ± 5.7 |
6.2 ± 5.9 |
ns |
| ⇔F6R3P9 |
PRL3D2 |
Growth hormone d6 |
PL-Iγ |
2 |
2 |
6.2 ± 5.7 |
6.2 ± 5.9 |
ns |
| O35256 |
PRL4A1 |
Prolactin-4A1 |
PLP-A |
2 |
2 |
6.3 ± 5.8 |
6.4 ± 5.8 |
ns |
| Q9CRB5 |
PRL7C1 |
Prolactin-7C1 |
PLP-O |
1 |
1 |
3.4 ± 3.0 |
5.6 ± 5.1 |
6.60E-03 |
The criteria for accepting protein identification included at least 1 unique peptide, peptide false discovery rate (FDR) <1%, and protein FDR <1%.
a ⇔: proteins indistinguishable from the protein above. b iBAQ: Log10 (protein intensity). c Based on Welch’s t-test, E17 vs. E18, p < 0.05, ns, no significance.
Although the main aim of performing DIA-MS was to examine the change in PRL family member peptide levels, we also identified 39 differentially expressed proteins (DEPs) with a fold-change ≥2 (Welch’s t-test, p < 0.05) (Table 2). Of those, 32 were upregulated, and 7 were downregulated in the E18 20:00 placentas (Table 2 and Fig. 4). Hierarchical clustering analysis was performed to assess expression similarities among the DEPs. The results are shown as a heatmap and dendrograms (Fig. S2A). The profile plots of the two selected clusters visualized a distinct behavior of the DEPs from each sample (Fig. S2B).
Table 2
Differentially expressed proteins between embryonic day 17 (E17) and E18 placentas
| UniProt |
Gene symbol |
Description |
Peptide count |
Unique peptides |
Mean iBAQa ± SE E17 20:00 |
Mean iBAQa ± SE E18 20:00 |
Foldb G18/G17 |
p-valuec |
| Up-regulated proteins in E18 placentas
(n = 32) |
| E9Q745 |
AOC1L2 |
Amine oxidase |
19 |
18 |
7.7 ± 6.8 |
8.0 ± 7.1 |
2.2 |
3.00E-02 |
| Q80YX1 |
TNC |
Tenascin |
18 |
18 |
6.8 ± 6.0 |
7.4 ± 6.5 |
3.5 |
1.50E-02 |
| Q04857 |
COL6A1 |
Collagen alpha-1(VI) chain |
12 |
12 |
7.0 ± 6.0 |
7.3 ± 6.3 |
2.2 |
4.30E-03 |
| Q9D952 |
EVPL |
Envoplakin |
12 |
12 |
6.6 ± 5.7 |
7.2 ± 6.3 |
3.4 |
2.60E-03 |
| Q3TVI8 |
PBXIP1 |
Pre-B-cell leukemia transcription factor-interacting protein 1 |
9 |
9 |
6.6 ± 5.3 |
6.9 ± 5.7 |
2.4 |
2.60E-03 |
| Q3V188 |
ENDOU |
Uridylate-specific endoribonuclease |
8 |
8 |
6.4 ± 5.7 |
7.4 ± 6.7 |
10.8 |
4.10E-02 |
| Q60790 |
RASA3 |
Ras GTPase-activating protein 3 |
8 |
8 |
5.9 ± 4.5 |
6.4 ± 5.0 |
3.1 |
3.10E-03 |
| Q8BSE0 |
RMDN2 |
Regulator of microtubule dynamics protein 2 |
6 |
6 |
5.9 ± 5.0 |
6.3 ± 5.5 |
2.9 |
1.10E-02 |
| P70180 |
NPR3 |
Atrial natriuretic peptide receptor 3 |
6 |
6 |
6.5 ± 5.7 |
6.9 ± 6.2 |
2.6 |
1.80E-02 |
| Q00175 |
PGR |
Progesterone receptor |
5 |
5 |
6.0 ± 5.3 |
6.5 ± 5.8 |
3.6 |
9.60E-03 |
| Q8CHT3 |
INTS5 |
Integrator complex subunit 5 |
4 |
4 |
5.4 ± 4.8 |
6.1 ± 5.5 |
5.4 |
4.80E-02 |
| Q8BMQ2 |
GTF3C4 |
General transcription factor 3C polypeptide 4 |
4 |
4 |
5.2 ± 4.7 |
6.1 ± 5.6 |
8.1 |
4.50E-02 |
| E9Q1P8 |
IRF2BP2 |
Interferon regulatory factor 2-binding protein 2 |
4 |
4 |
4.7 ± 4.0 |
5.8 ± 5.0 |
11.1 |
4.70E-03 |
| P59384 |
ADAMTS15 |
A disintegrin and metalloproteinase with thrombospondin motifs 15 |
4 |
4 |
5.3 ± 3.9 |
6.4 ± 5.1 |
14.5 |
6.20E-03 |
| Q9EPW0 |
INPP4A |
Inositol polyphosphate-4-phosphatase type I A |
4 |
4 |
5.8 ± 5.1 |
6.2 ± 5.5 |
2.5 |
4.70E-02 |
| P58404 |
STRN4 |
Striatin-4 |
3 |
3 |
5.4 ± 4.8 |
6.5 ± 5.9 |
12.1 |
3.50E-02 |
| Q99KX1 |
MLF2 |
Myeloid leukemia factor 2 |
3 |
3 |
6.0 ± 4.8 |
6.3 ± 5.1 |
2.1 |
2.90E-03 |
| P21460 |
CST3 |
Cystatin-C |
3 |
3 |
7.0 ± 5.9 |
7.3 ± 6.2 |
2 |
4.60E-02 |
| Q8R3L2 |
TCF25 |
Transcription factor 25 |
3 |
3 |
5.7 ± 5.0 |
6.3 ± 5.6 |
4.6 |
4.90E-02 |
| Q9CR50 |
RCHY1 |
RING finger and CHY zinc finger domain-containing protein 1 |
2 |
2 |
5.3 ± 4.5 |
5.7 ± 4.9 |
2.2 |
4.60E-02 |
| Q7TQK4 |
EXOSC3 |
Exosome complex component RRP40 |
2 |
2 |
5.2 ± 4.6 |
5.9 ± 5.3 |
4.8 |
3.20E-02 |
| Q8K1S3 |
UNC5B |
Netrin receptor UNC5B |
2 |
2 |
5.2 ± 4.4 |
6.0 ± 5.2 |
5.5 |
3.60E-02 |
| P62823 |
RAB3C |
Ras-related protein Rab-3C |
2 |
2 |
5.3 ± 5.0 |
9.1 ± 8.8 |
6,857.2 |
1.20E-02 |
| P35276 |
RAB3D |
Ras-related protein Rab-3D |
2 |
2 |
5.6 ± 5.3 |
9.1 ± 8.8 |
3,696.1 |
1.80E-02 |
| Q6P5C5 |
SMUG1 |
Single-strand selective monofunctional uracil DNA glycosylase |
2 |
2 |
4.7 ± 3.4 |
6.1 ± 4.8 |
25.9 |
1.60E-02 |
| Q9CRB5 |
PRL7C1 |
Prolactin-7C1 |
1 |
1 |
4.4 ± 3.9 |
5.6 ± 5.1 |
14.4 |
6.60E-03 |
| D7PDD4 |
MPIG6B |
Megakaryocyte and platelet inhibitory receptor G6b |
1 |
1 |
4.7 ± 4.3 |
5.7 ± 5.3 |
10.4 |
1.40E-02 |
| P51906 |
SLC1A1 |
Excitatory amino acid transporter 3 |
1 |
1 |
4.8 ± 4.2 |
5.3 ± 4.8 |
3.3 |
3.20E-02 |
| Q91VL8 |
TERF2IP |
Telomeric repeat-binding factor 2-interacting protein 1 |
1 |
1 |
4.7 ± 3.4 |
5.8 ± 4.6 |
12.9 |
3.70E-06 |
| P34960 |
MMP12 |
Macrophage metalloelastase |
1 |
1 |
4.6 ± 3.3 |
5.6 ± 4.3 |
8.9 |
3.20E-02 |
| Q8BGH4 |
REEP1 |
Receptor expression-enhancing protein 1 |
1 |
1 |
4.7 ± 3.9 |
5.6 ± 4.8 |
7 |
1.40E-02 |
| P15066 |
JUND |
Transcription factor jun-D |
1 |
1 |
4.6 ± 4.0 |
5.7 ± 5.1 |
14.3 |
6.60E-04 |
| Down-regulated proteins in E18 placentas
(n = 7) |
| Q8CB44 |
GRAMD4 |
GRAM domain-containing protein 4 |
9 |
9 |
8.3 ± 7.4 |
6.8 ± 5.8 |
0 |
1.60E-04 |
| P25206 |
MCM3 |
DNA replication licensing factor MCM3 |
9 |
9 |
6.3 ± 5.3 |
5.8 ± 4.7 |
0.3 |
3.60E-02 |
| P51661 |
HSD11B2 |
Corticosteroid 11-beta-dehydrogenase isozyme 2 |
7 |
7 |
7.1 ± 6.3 |
6.5 ± 5.7 |
0.3 |
3.20E-02 |
| Q3UA06 |
TRIP13 |
Pachytene checkpoint protein 2 homolog |
7 |
7 |
6.8 ± 6.1 |
6.4 ± 5.8 |
0.4 |
2.60E-02 |
| P02089 |
HBB-B2 |
Hemoglobin subunit beta-2 |
6 |
1 |
7.1 ± 6.3 |
6.7 ± 5.9 |
0.4 |
2.20E-02 |
| Q91Y86 |
MAPK8 |
Mitogen-activated protein kinase 8 |
2 |
1 |
5.4 ± 4.5 |
5.1 ± 4.2 |
0.5 |
1.80E-02 |
| Q6P6M5 |
PEX11G |
Peroxisomal membrane protein 11C |
2 |
1 |
6.3 ± 5.4 |
5.9 ± 4.9 |
0.3 |
2.50E-03 |
The criteria for accepting protein identification included at least one unique peptide, peptide false discovery rate (FDR) <1%, and protein FDR <1%.
a iBAQ: Log10 (protein intensity). b Fold change from E17 to E18. c Based on Welch’s t-test, E17 vs. E18, p < 0.05.
We performed GO enrichment analysis and identified that “extracellular matrix disassembly,” “elastin catabolic process,” “cellular response to metal ion,” “female pregnancy,” and “cellular response to stress” were the most significantly enriched “biological process” (Fig. S2C). Two cellular component GO annotations and four molecular function GO annotations were significantly enriched (Fig. S2C). The proteins enriched in each GO annotation are shown (Fig. S2D).
Discussion
In the present study, we confirmed a sharp decline of PRL3B1 in the maternal plasma of C57BL/6 strain mice between G18 8:00 and G18 12:00, more than 12 hrs prior to parturition (Fig 1A). The PRL secretion patterns were almost identical to previous studies (Fig. 1B) [11, 19] However, our results for PRL3B1 significantly conflicted with those of Soares and Talamantes, where their study showed a plateau in serum PRL3B1 levels from G14 until delivery [11], we detected a sharp decline (Fig. 1A). We speculate the difference originates in the PRL3B1 purification process. They used many mouse placenta samples and extracted PRL3B1 from the electrophoresed gel bands [45]. This was performed before other PRL family members, including PRL3D1, were identified in the mouse placenta [10, 11, 45, 46]. It is possible that PRL family members were contaminated since most of those proteins were detected in the placenta (Table 1). Contamination commonly causes cross-reaction or interference in immunoassays [47]. In our methodology, we used ELISA kits coated with anti-PRL3B1 antibodies synthesized from purified recombinant PRL3B1 (using Escherichia coli) as an antigen to minimize the risk of contamination. As a consequence, we detected a sharp decline of PRL3B1.
Interestingly, we found that the rapid decrease of PRL3B1 coincided with the PRL surge (Fig. 1). We suspect the primary source of PRL signal transitions from the placenta back to the hypothalamus-pituitary neuroendocrine system before the end of pregnancy. In rats, PRL3B1 peaks at G19 and decreases steadily until labor at G21 [48-50], while the prepartum PRL surges between G20 18:00 and G20 0:00 [51]. Thus, our results (Fig. 1A) suggest that mice may have a similar prepartum PRL3B1 decline and affirm that rodents share a similar reproductive endocrine profile. PRL secretion returning to the pituitary gland from the placenta may be essential in the physiological transition from pregnancy to motherhood, such as nurturing the pups through lactation [5, 6, 52]. Moreover, because murine have a postpartum estrus that enables a seamless gestation [53], pituitary PRL is required to establish this probable subsequent pregnancy [7, 8].
The mechanism causing the rapid decrease in prepartum plasma PRL3B1 is unknown. In rats, serum P4 withdrawal seems to correlate with the decline of PRL3B1 serum (or plasma) concentration [20, 48-51, 54]. In mice strains, serum P4 levels decline at G17 and diminish by G18 [11, 55, 56], and here we show the P4 decline precedes the PRL3B1 drop for the first time in mice (Figs. 1A and 2). We speculate that P4 is one of the regulatory factors of PRL3B1 secretion, based on the report that exogenous P4 led to PRL3B1 over-secretion in rats [57], and evidence that regression of maternal P4 triggers the prepartum PRL surge [51, 58, 59]. We think it is less likely that PRL3B1 is affected by PRL, as previous studies show that prepartum PRL3B1 and PRL do not exert direct negative feedback to suppress each other [51, 60, 61]. Thus, it could be interesting if P4 were the regulatory factor of the PRL axis shift, but this hypothesis requires further investigation to be proven.
In mice, luteolysis is triggered by prostaglandin F2α (PGF2α), reducing the expression of PRLR in the corpus luteum [62, 63]. Hence, a high PRL3B1 plasma concentration or the exogenous PRL injection cannot prevent luteolysis, the P4 decline, and parturition [19, 64]. Our results (Figs. 1A and 2) do not contradict this theory.
We found Prl3b1 mRNA levels to be stable until delivery (Fig. 3), dissociating with the plasma PRL3B1 level (Fig. 1A). This suggests that conventional methods of examining mRNA levels may not be suited to measure PRL family protein expression and secretion [4, 15]. Based on a report showing a concurrent decrease in PRL3B1 protein levels in rat placenta and PRL3B1 secretion [50], we analyzed the placenta proteomic profile expecting to detect PRL3B1 and PRL family regression. Contrary to our expectation, the protein content of PRL3B1 and other PRL family members showed no significant change in expression except PRL7C1 (Table 1). Therefore, our overall results (Figs. 3 and 5) suggest that PRL3B1 and most of the PRL family production may be stalled in the placenta during the last day of pregnancy. This indicates that the secretion of PRL3B1 from the placenta is suppressed in prepartum dams. Evidence suggests endocrine and/or paracrine factors such as epidermal growth factor (EGF), interleukin 6 (IL-6), and tumor necrosis factor-alpha (TNFα) inhibit PRL3B1 secretion during mid to late pregnancy [59, 65-67].
Alongside PGF2α, EGF, IL-6, and TNFα are thought to determine the timing of labor in rodents, possibly by regulating the process of luteolysis [68-70] and uterine contraction [71]. PRL is also an immunomodulatory cytokine that regulates the expression of inflammatory cytokines like IL-6 and TNFα in some conditions [72, 73]. Thus, the prepartum endocrine profile and the inter-relation of PRL, P4, EGF, and other cytokines signals are complicated [74]. Further investigation would unravel how the decline of placental PRL3B1 secretion (Fig. 1A) relates to the cascade reaction required for normal labor.
Besides PRL3B1, other PRL family members’ mRNA (Prl2a1, Prl7b1, Prl4a1, Prl5a1, Prl5a2, and Prl6a1) is produced in TGCs and trophoblasts embedded deep in the uterine-placental interface (e.g., metrial gland) [16, 75]. Since measuring these proteins expressed outside the placenta was not feasible, our DIA-MS results are limited to the PRL-like proteins in the placenta (Table 1 and Fig. 5).
General knowledge of the PRL family is severely lacking. Currently, no PRL family members are confirmed as PRLR ligands other than PRL3B1 and PRL3D1, nor are they confirmed as hormones that enter the maternal circulation [3, 14]. We do not know their regulatory factors [15]. As for PRL7C1, we do not have the means to measure plasma concentration. There is no report of PRL7C1 function, except one study that suggests PRL7C1 involvement in neonatal uterus development [76]. Simmons et al. showed a slight increase in Prl7c1 mRNA level in the G18.5 mouse placenta [15]. However, the reason why PRL7C1 and its mRNA levels increase in the prepartum placenta is unknown. Thus, our results offer additional insight to elucidate the functions of PRL7C1 and the diversified murine PRL family.
Lastly, analysis of the DIA-MS results revealed 39 DEPs between E17 20:00 and E18 20:00 placentas (Table 2 and Fig. 4). Besides PRL7C1, P4 receptor (PGR) might be the most relevant DEP to the PRL family expression due to their physiological connections [51, 64] and related biological process classified in “female pregnancy” (Fig. S2C and S2D). Three isoforms of PGR are explicitly expressed in stromal cells of the decidua basalis of the rat placenta from mid to late pregnancy [77]. Though no report has focused on the prepartum mice placenta, based on the timing we observed, the upregulation of PGR (Fig. 4) might be a counter-response to the decline of P4 (Fig. 2). Although we could not find a solid connection between the DEPs and the PRL family, our MS results (Table S1 and Fig. S2) might be helpful for further understanding of the terminal placenta.
Conclusive results of the present study are depicted in the schema (Fig. 6). We hypothesize that the decline of PRL3B1 secretion from the mouse placenta indicates its functional endpoint as an endocrine organ. Hence, it might be a valuable cue to predict parturition. Moreover, there should be drastic changes in the endocrine communication between the placenta and maternal organs, such as the PRL surge from the anterior pituitary gland [51, 61]. We hypothesize the autocrine and paracrine signals of PRL3B1 at the feto-maternal interface may function differently from the remote pituitary PRL. Although PRL may be the only hormonal signal that retains its high levels throughout pregnancy, parturition, and lactation in mice [3, 5], there is yet to be a clear understanding of all its functions. We hope our findings lead to discovering novel physiological functions of the PRL family and the prepartum placenta as a critical bridge between gestation, labor, and motherhood.
Acknowledgments
We thank Dr. Hideru Obinata and Dr. Touko Hirano (Laboratory of Analytical Instruments, Education and Research Support Center, Gunma University, Japan) for their technical advice on mass spectrometry. We thank the staff of the Department of Integrative Physiology, Gunma University Graduate School of Medicine, Japan, for all the support. We thank Dr. Tsuyoshi Nakanishi for the discussion. We thank Dr. Tomoko Sairenji for proofreading.
Author Contributions
TJS, SM, YF, NS, and NK designed the study. TJS, SM, and OKE collected the samples. TJS, YH, MM, HY, and TA performed formal analysis. TJS performed data analysis and wrote the first draft of the manuscript. YF, NS, and NK supervised the study. All authors contributed to the manuscript revision and approved the submitted version.
Disclosure
Fundings
This work was funded by Grant-in-Aid for Scientific Research (21J15858 to TJS) from the Japan Society for the Promotion of Science (JSPS) and The Japanese Society for Pediatric Endocrinology Future Development Grant supported by Novo Nordisk Pharma Ltd to TJS.
Conflict of interest (COI)
The authors declare that the research was conducted without any commercial or financial relationship that could be construed as a potential conflict of interest. Noriyuki Koibuchi is a member of Endocrine Journal’s Editorial Board.
Data availability statement
The data supporting this study’s findings are available from the corresponding author upon reasonable request.
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