Abstract
Gestational diabetes mellitus (GDM) is a condition of diabetes with onset or first recognition in pregnancy. Its incidence is increasing, and GDM deleteriously affects both mother and the fetus during and even after pregnancy. Previous studies in mice have shown that during pregnancy, β-cell proliferation increases in the middle and late stages of pregnancy and returns to normal levels after delivery. Hormones, such as prolactin, estradiol, and progesterone as well as protein kinases, play important roles in regulating gestation-mediated β-cell proliferation; however, the regulatory relationship between them is uncertain. We previously found that protein kinase Pbk was crucial for basal proliferation of mouse islet cells. Herein we show that Pbk is upregulated during pregnancy in mice and Pbk kinase activity is required for enhanced β- cell proliferation during pregnancy. Notably, knock-in (KI) of a kinase-inactivating Pbk mutation leads to impaired glucose tolerance and reduction of β-cell proliferation and islet mass in mice during pregnancy. Prolactin upregulates the expression of Pbk, but the upregulation is diminished by knockdown of the prolactin receptor and by the inhibitors of JAK and STAT5, which mediate prolactin receptor signaling, in β-cells. Treatment of β-cells with prolactin increases STAT5 binding to the Pbk locus, as well as the recruitment of RNA polymerase II, resulting in increased Pbk transcription. These results demonstrate that Pbk is upregulated during pregnancy, at least partly by prolactin-induced and STAT5-mediated enhancement of gene transcription, and Pbk is essential for pregnancy-induced β-cell proliferation, increase in islet mass, and maintenance of normal blood glucose during pregnancy in preclinical models. These findings provide new insights into the interplay between hormones and protein kinases that ultimately prevent the development of GDM.
Introduction
Gestational diabetes mellitus (GDM), which is increasing in incidence, occurs during pregnancy with impaired glucose tolerance. GDM has a deleterious impact on the life of the mother and fetus both during and after pregnancy. GDM will affect approximately 15% of pregnant women in Australia (Casagrande et al. 2018). According to the eighth edition of the diabetes map released by the International Diabetes Federation (IDF) in December 2017, the number of affected newborns has reached 210 million. It is thus of great significance to study its molecular pathogenesis and aid in development of novel treatments for this condition. Pregnancy is a unique physiological state that requires expansion of pancreatic β-cells to increase insulin output to meet the demand of the increased metabolism. During pregnancy in rodents (Halban et al. 2014) and humans (Butler et al. 2010), the expansion of pancreatic islets indicates that the adaptive growth of pancreatic islets is a mechanism for maintaining the balance of metabolism for pregnancy, which is a physiological state characterized by increased insulin demand. Failure of the adaptive β-cell expansion leads to an imbalance of glucose homeostasis and can lead to the development of GDM.
Previous studies in mice have shown that this adaptive increase in insulin production during pregnancy is accomplished both through enhanced insulin secretion by β-cells proliferation and expansion (Sorenson & Brelje 1997). During pregnancy in mice, β-cell mass increases two-fold and β-cell proliferation reaches its peak in the middle and late stages of pregnancy, with the proliferation rate returning to normal levels after delivery (Karnik et al. 2007). This β-cell expansion likely occurs through enhanced proliferation, including possible regeneration from precursor cells, achieving a compensatory increase in the number of β-cells (Hartmann & Cregan 2001, Ben-Haroush et al. 2004, Harreiter et al. 2014). Therefore, β-cell dysfunctional proliferation as a potential mechanism of gestational diabetes is the focus of further research.
During pregnancy, maternal pancreatic β-cell mass undergoes a compensatory expansion and secretes more insulin to maintain glucose homeostasis, which is continually challenged by weight gain and increasing insulin resistance (Xue et al. 2010). Hormones play a crucial role in this process, especially prolactin. Increased β-cell proliferation coincides with the increase in prolactin (PRL) and/or placental lactogen, and PRL has been shown to be essential for the enhancement of β-cell proliferation and function during pregnancy (Rieck & Kaestner 2010). After binding to the PRL-receptor (PRL-R), PRL can promote β-cell proliferation via Janus kinase 2 (JAK2)-signal transducer and activator of transcription 5 (STAT5), phosphatidylinositol 3-kinase (PI3K)-AKT, and MAPK-extracellular regulated protein kinase (ERK) pathways (Amaral et al. 2004, Brelje et al. 2004, Rieck et al. 2009).
Postsynaptic density-95/Discs large/zonula occludens-1 (PDZ)-binding kinase (Pbk), a member of the serine/threonine kinases, is identified as a mitogen-activated protein kinase kinase (MAPKK) (Sivan et al. 1997, Catalano et al. 1999). Previous studies have shown that Pbk plays a key role in the proliferation of different cell lines (Hu et al. 2010, Joel et al. 2015), especially tumor cells. Pbk can be phosphorylated by cyclin-dependent kinase (Cdk)1/cyclin B complex and induces cell proliferation through activating p38 mitogen-activated protein kinase (MAPK), Erk, and phosphoinositide 3-kinase (PI3K), or inactivate p53 (Matsumoto et al. 2004, Fujibuchi et al. 2005, Kim et al. 2012). In our previous studies, we found that inhibition of the nuclear scaffold protein menin with a small molecule menin inhibitor (MI) improved hyperglycemia in HFD-induced diabetic mice, through interrupting the menin/JunD/Pbk axis and promoting β-cell proliferation (Ma et al. 2021). Pbk expression is correlated to the expansion of islets during pregnancy (Uesato et al. 2018). However, it is not yet known whether Pbk has any impact on prolactin-induced β-cell proliferation and if so, the underlying mechanism. In the present studies, we generated dysfunction Pbk kinase mutant KI mice and evaluated the impact of Pbk on GDM. We found that prolactin treatment enhanced the enrichment of STAT5 at the Pbk promoter, and then upregulated Pbk expression, correlating with the increased β-cell proliferation and islet mass during pregnancy.
Materials and methods
Mice husbandry, breeding, and experimentation
All mouse experiments implemented in this study followed the NIH Guide for the Care and Use of Laboratory Animals and also according to the IACUC standards following ethics approval by the animal committee at the University of Pennsylvania (UPenn). Eight-week-old C57BL/6J (Stock number 000664 from JAX laboratory) female mice and male mice for breeding were purchased from Jackson Labs. Eight-week-old PbkKI/KI female mice whose background were also C57BL/6J mice were generated working with the CRISPR Editing Core and Transgenic Care at UPenn. The was introduced to the endogenous locus via CRISPR/Cas9-mediated genome editing, in fertilized mouse eggs. By extracting DNA from the tail of PbkKI/KI mice and amplifying it with specific primers, the PCR products were sequenced to confirm the presence of mutant gene locus and the homozygous gene monic PbkKI/KI with Pbk inactivation was obtained (Ma et al. 2021). PbkKI/KI female mice under this study are fifth or sixth generations.
We set up two groups of mice, that is, WT and mutant Pbk group, with eight mice, 10 weeks old, per group. The WT and mutant Pbk mice each were separated into four groups randomly, that is, WT non-pregnant or pregnant groups and mutant Pbk non-pregnant or pregnant groups (four mice/group).
PbkKI/KI and control females were mated with WT males. Vaginal plugs were scored at gestational day (GD) 0.5 and males removed. All the mice were housed in a specific pathogen-free facility with a 12 h light:12 h darkness cycle at room temperature.
Culture of cell lines
Mouse pancreatic islet-derived Men1 Excisable cells (PIME cells) were isolated from a Men1fl/fl Cre-ER mice (Yang et al. 2010, Ma et al. 2021). Men1 gene is present in WT PIME cells and could be inducibly deleted after TAM treatment. HEK293T cells were purchased from American Type Culture Collection (ATCC). Both cell lines were cultured in Dulbecco’s Modified Eagle’s Medium (DMEM) with 10% (v/v) FBS, 100 units/mL penicillin, and 100 μg/mL streptomycin.
INS-1 cells, a rat insulinoma cell line, were cultured in RPMI 1640 supplemented with 2 mM L-glutamine, 1 mM sodium pyruvate, 10% (v/v) FBS, 10 mM HEPES, 100 units/mL penicillin, 100 μg/mL streptomycin, and 50 μM β-mercaptoethanol. Cells were cultured in a humidified incubator at 37°C with 5% CO2.
Fasting blood glucose test
In order to measure fasting blood glucose, the blood was taken from 1 mm of clipped tail of mice with a glucometer and disposable test strips (One Touch Lifescan, Malvern, PA, USA). The mice were fasted overnight (16 h) before the start of testing fasting blood glucose.
Intraperitoneal glucose tolerance test (GTT)
The intraperitoneal glucose tolerance test (GTT) was performed on mice to evaluate their glucose tolerance. The mice were fasted overnight (16 h) and weighed bodyweight. Blood glucose was measured from tail vein blood at baseline (time 0) and then administrated with glucose (2 g dextrose/kg bodyweight) by IP injection. After injection, blood glucose was measured at 15, 30, 60, 90, and 120 min with a hand-held glucometer and disposable test strips (One Touch Lifescan, Malvern, PA,, USA).
Insulin tolerance test (ITT)
The insulin tolerance test (ITT) was performed on mice to evaluate their insulin tolerance. The mice were fasted overnight (6 h) and their bodyweight was weighed. Blood glucose was measured from tail vein blood at baseline (time 0) and then administrated with insulin (0.75 U/kg) delivered in 1 mL/kg saline by IP injection. After injection, blood glucose was measured at 15, 30, 45, and 60 min with a hand-held glucometer and disposable test strips (One touch).
GSIS assays ex vivo
Insulin release function of the isolated mouse islets in response to glucose stimulation was tested by Islet Cell Biology Core at UPenn using an automated perifusion system. After 2 days of incubation in PRMI1640 media with 10% FBS, 1% SP, 1% glutamine, and 10 mM glucose at 37°C with 5% CO2, islets were moved into the perifusion system and subjected to 0 and 3mM glucose concentration at 0, 15, and 30 min, respectively. Insulin was harvested automatically and measured by RIA and Biomarkers Core at UPenn using the ELISA method.
Generation of gene knock down, overexpression, mutant, and complemented cell lines
Prlr shRNAs were co-transfected with retroviral packaging pMD2.G and psPAX2 (Sigma) plasmid into HEK293 cells using the calcium chloride precipitation method, and the resulting recombinant virus was used to transduce PIME cells, as previously reported (Yang et al. 2010, Feng et al. 2017). All lentiviral shRNA plasmids were derived from a pLKO.1-puromycin backbone. shRNA plasmids of prlr were obtained from the University of Pennsylvania Perelman School of Medicine High-Throughput Screening Core. Specific shRNA sequences are as follows:
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CCACCAATTATTCATTGACAT
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CTGTTTCTTTAGCAAGCAGTA
A pMX-puro-Pbk construct, as previously published, and a mutant plasmids with K64K65 to AA based on pMX-puro-Pbk construct were transfected into INS-1 and PIME cell line to induce ectopic expression of Pbk.
Cells were transduced by the virus of choice in the presence of 4 μg/mL polybrene (hexadimethrine bromide) for lentivirus infection. Then, 24 h after completion of transduction, cells were selected with puromycin or blasticidin for 72 h.
Drug treatment on cell lines
For testing Pbk expression, INS-1 cells, PIME cells, and prlr knockdown PIME cells were treated with prolactin at different concentrations, that is, 0, 0.1, 0.3, 1 ng/mL, for 24 h. Cells were then harvested for RNA extraction for qRT-PCR and Western blot. PIME cells were treated with estradiol and progesterone at different concentrations for 24 h. Cells were then harvested for RNA extraction for Western blot.
To make sure prolactin treatment induces Pbk expression through JAK-STAT pathway, PIME cells were treated with fedratinib at 2.5 μM and STAT5 inhibitor at 30 μM for 24 h. Cells were then harvested for RNA extraction for qRT-PCR and Western blot.
Cell growth curve, MTS assay, and cell death detection
INS-1 cells and PIME cells transfected with vector, WT Pbk, and mutant Pbk expression plasmids were seeded at 5 × 104 or 1 × 105 cells per well in triplicate in 12-well plates, and cells were counted at the indicated days and drawn cell growth curves.
As for the MTS assay and cell death detection, INS-1 cells and PIME cells transfected with vector, WT Pbk, and mutant Pbk expression plasmids were plated in a 96-well plate at a density of 1 × 104 cells/well with 12 replicate wells. INS-1 cells and PIME cells were cultured 3 days and 4 days separately. Then, the MTS [3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium] assay kit (Promega) was utilized to six-well cells to assess cell growth and was performed according to the manufacturer’s instructions. Absorbance of each well was measured at 490 nm using an ELISA plate reader (SpectraMax M2, Molecular Devices). At the same time, another six-well cells were collected via trypsin treatment and washed twice using PBS. Then, the cells were stained using PI with concentration of 1 µg/mL for 1 min and were examined by flow cytometry (BD accuri C6 flow cytometer, BD Biosciences). Data were analyzed using FlowJo software.
Western blot analysis
Cultured cell lines were collected and lysed with RIPA buffer containing protease and phosphatase inhibitors. Protein concentrations were determined using a BCA assay kit (Thermo Scientific). Following electrophoresis on 4–12% Bis-Tris Plus Blot SDS-PAGE gels (GenScript), protein was transferred to PVDF membranes (Life Technologies). Blocking was performed in TBST containing 5% non-fat dry milk based on the manufacturer’s blocking instructions. The details of antibodies including first antibodies and second antibodies used for WB assay in this study are listed. The proteins were visualized by detection with AMER sham ECL Western blotting detection reagents (GE Healthcare). Protein bands were analyzed using ImageJ software.
Immunofluorescence staining of pancreas sections
Mice were dissected to obtain pancreas samples. Pancreas samples were fixed in 4% paraformaldehyde in PBS at room temperature and then embedded in paraffin. The sections were deparaffinized and processed in high-pressure oven in Tris-EDTA buffer (pH 9) for 2 h to recover antigen. After washing three times with PBS for 5 min each time, the sections were blocked for 1 h at room temperature with blocking buffer (5% goat serum, 0.05% Tween-20 in PBS) followed by incubation with primary antibodies overnight at 4°C at room temperature. After washing three times with PBS, sections were then incubated with corresponding secondary antibodies (1:200) and DAPI (Roche) for 1 h at room temperature. The sections were visualized using a Nikon Eclipse E800 fluorescent microscope with a CCD digital camera.
To avoid bias during imaging and selecting sections, the samples were blinded by randomly numbering samples to avoid group-related information, prior to moving to next step of analysis including staining the sections and collecting the image. The quantification analysis of the positive staining images was carried out using ImageJ software.
β-Cell mass calculation
After weighing, the pancreas was fixed, embedded in optimal cutting temperature compound, and then frozen. β-cell mass was measured using ImageJ software to quantify insulin+ and total pancreas area in each section. The six different sections of each mouse pancreas were measured. β-cell area was determined by insulin staining area observed using a microscope (DMI6000B, Leica) with whole section scanning function. The six different sections from each pancreas sample were sequentially cut with each section separated by at least 250 μm. β-cell area was the average of six measured sections. The calculated β-cell mass = (β-cell area/total pancreas area) × (total pancreas weight).
Proliferation index analysis
To measure proliferation, we immunoassayed sections using antibodies against insulin and BrdU+ and the proportion of BrdU+β-cells calculated as a percentage. Insulin+ cells showing nuclear DAPI staining were considered as β-cells. Insulin+ cells showing nuclear co-localized staining for DAPI+ and BrdU+ were counted as proliferating β-cells. The proliferation index = (Ins+ and BrdU+/whole insulin+ cells with DAPI staining) × 100%.
Gene expression analysis by quantitative RT-PCR
Total RNA was isolated from cultured cells using Trizol (Invitrogen) and RNeasy Mini Kit (Qiagen). RNA (1.0 ug) was reverse transcribed into cDNA and real-time PCR (RT-PCR) was performed using a Quantitative SYBR-Green PCR Kit (Qiagen) and a 7500 Fast Real Time PCR System (Applied Biosystems). Assays were performed in technical replicates and normalized to mouse actin as a reference standard.
Chromatin immune precipitation (ChIP) assay
ChIP assays were performed using a QuickChIP™ kit (Novus Biologicals) according to the manufacturer’s instructions. Approximately 5 × 106 cells were used for each immunoprecipitation. Briefly, cells were cross-linked by adding formaldehyde to final concentration of 1% and lysed in a ChIP lysis buffer with protease inhibitors, and cellular DNA was sheared with sonication. Then, the lysate was incubated with either control IgG or a specific primary antibody (4 μg) at 4°C overnight and collected with protein G agarose beads. The protein-DNA complexes were eluted from the beads and incubated at 65°C overnight to break the protein-DNA crosslinking. DNA was amplified by real time PCR using primer pairs detecting indicated genes and SYBR Green reaction mix (Qiagen). Specific primer sequences are as follows:
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Primer 0 F: 5’-GAGTCTGTGAGTGATCTCCATTT-3’
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0 R: 5’-GTCACTGTTGGAAATCTGTGCTC-3’
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Primer 1F: 5’-CAATTCCTCAGCTAGCCCCCT
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1 R: 5’-CTGATGCAAACTGCAAGAGGT
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Primer 2 F: 5’-CAGAGCCTGGCCTTCTGATTT
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2 R: 5’-GTGTGTGTGTGTGTTTGTGCT
Each assay was implemented in duplicates and the mean normalized to input chromatin and reported as percent input.
Immunofluorescence staining
Quantifications of proliferation marker BrdU ,Pbk expression,and insulin staining area in PbkWT/WT and PbkKI/KI pregnant or non-pregnant mice are showed by IF staining. Each marker was quantified in β-cells from 10 islets of each mouse (4 mice/group, 40 islets total per group), and data are represented as average percent positive cells per islet for each mouse ± s.e.m. Insulin staining area was quantified on six pancreas sections of each mouse (four mice/group, each section was whole scanned and scored) and the data are represented as average ratio of insulin staining area over whole pancreas staining area (DAPI stained area) ± s.e.m. All comparisons for the mouse IF data were analyzed for statistical significance by unpaired two-tailed t-tests and statistics were computed using GraphPad Prism6 (Yang et al. 2010).
The upregulation of Pbk in β-cells of mice during pregnancy was crucial for cell proliferation. (A and B) Representative images of double staining for insulin (green) and Pbk (red) in islets from non-pregnant (A) or pregnant (B) C57BL/6 mice. Nuclei were labeled by DAPI (blue). Scale bar: 50 μm; (C) Quantification of Pbk positive β-cells. Data are represented as percentage of insulin/Pbk double positive cells from C57BL/6 female control and pregnant group. Four mice for each group and at least ten islet images per mouse were analyzed. **P < 0.01 (two-tailed Student’s t-test). (D) WB results for Pbk (V5) protein in INS-1 cells transfected with vector, WT Pbk, or mutant Pbk-expressing plasmids. (E) Cell growth curves of INS-1 cells transfected with vector, WT Pbk, or mutant Pbk expression plasmids (n = 3). ***P < 0.001 (two‐way ANOVA, transfection construct, and time are two categorical variables). ns, not statistically significant difference. (F) Cell growth of INS-1 cells transfected with vector, WT Pbk, or mutant Pbk expression plasmids was assessed by MTS assay. **P < 0.01, *P < 0.05 (one‐way ANOVA). ns, not statistically significant difference. (G) Cell death analysis via PI staining followed by flow cytometry for INS-1 cells transfected with vector, WT Pbk, or mutant Pbk expression plasmids. ns, not statistically significant difference (one‐way ANOVA). (H) WB results for Pbk expression in PIME cells transfected with vector, WT Pbk, or mutant Pbk-expressing plasmids. (I) Cell growth curves of PIME cells transfected with vector, WT Pbk, or mutant Pbk expressing plasmids (n = 3). ***P < 0.001 (two‐way ANOVA, transfection construct and time are two categorical variables). ns, not statistically significant difference. (J) Cell growth of PIME cells transfected with vector, WT Pbk, or mutant Pbk expression plasmids was assessed by MTS assay. **P < 0.01, *P < 0.05 (one‐way ANOVA). ns, not statistically significant difference. (K) Cell death analysis via PI staining followed by flow cytometry for PIME cells transfected with vector, WT Pbk, or mutant Pbk expression plasmids. ns, not statistically significant difference (one‐way ANOVA).
Citation: Journal of Endocrinology 252, 2; 10.1530/JOE-21-0114
The upregulation of Pbk in β-cells of mice during pregnancy was crucial for cell proliferation. (A and B) Representative images of double staining for insulin (green) and Pbk (red) in islets from non-pregnant (A) or pregnant (B) C57BL/6 mice. Nuclei were labeled by DAPI (blue). Scale bar: 50 μm; (C) Quantification of Pbk positive β-cells. Data are represented as percentage of insulin/Pbk double positive cells from C57BL/6 female control and pregnant group. Four mice for each group and at least ten islet images per mouse were analyzed. **P < 0.01 (two-tailed Student’s t-test). (D) WB results for Pbk (V5) protein in INS-1 cells transfected with vector, WT Pbk, or mutant Pbk-expressing plasmids. (E) Cell growth curves of INS-1 cells transfected with vector, WT Pbk, or mutant Pbk expression plasmids (n = 3). ***P < 0.001 (two‐way ANOVA, transfection construct, and time are two categorical variables). ns, not statistically significant difference. (F) Cell growth of INS-1 cells transfected with vector, WT Pbk, or mutant Pbk expression plasmids was assessed by MTS assay. **P < 0.01, *P < 0.05 (one‐way ANOVA). ns, not statistically significant difference. (G) Cell death analysis via PI staining followed by flow cytometry for INS-1 cells transfected with vector, WT Pbk, or mutant Pbk expression plasmids. ns, not statistically significant difference (one‐way ANOVA). (H) WB results for Pbk expression in PIME cells transfected with vector, WT Pbk, or mutant Pbk-expressing plasmids. (I) Cell growth curves of PIME cells transfected with vector, WT Pbk, or mutant Pbk expressing plasmids (n = 3). ***P < 0.001 (two‐way ANOVA, transfection construct and time are two categorical variables). ns, not statistically significant difference. (J) Cell growth of PIME cells transfected with vector, WT Pbk, or mutant Pbk expression plasmids was assessed by MTS assay. **P < 0.01, *P < 0.05 (one‐way ANOVA). ns, not statistically significant difference. (K) Cell death analysis via PI staining followed by flow cytometry for PIME cells transfected with vector, WT Pbk, or mutant Pbk expression plasmids. ns, not statistically significant difference (one‐way ANOVA).
Citation: Journal of Endocrinology 252, 2; 10.1530/JOE-21-0114
The upregulation of Pbk in β-cells of mice during pregnancy was crucial for cell proliferation. (A and B) Representative images of double staining for insulin (green) and Pbk (red) in islets from non-pregnant (A) or pregnant (B) C57BL/6 mice. Nuclei were labeled by DAPI (blue). Scale bar: 50 μm; (C) Quantification of Pbk positive β-cells. Data are represented as percentage of insulin/Pbk double positive cells from C57BL/6 female control and pregnant group. Four mice for each group and at least ten islet images per mouse were analyzed. **P < 0.01 (two-tailed Student’s t-test). (D) WB results for Pbk (V5) protein in INS-1 cells transfected with vector, WT Pbk, or mutant Pbk-expressing plasmids. (E) Cell growth curves of INS-1 cells transfected with vector, WT Pbk, or mutant Pbk expression plasmids (n = 3). ***P < 0.001 (two‐way ANOVA, transfection construct, and time are two categorical variables). ns, not statistically significant difference. (F) Cell growth of INS-1 cells transfected with vector, WT Pbk, or mutant Pbk expression plasmids was assessed by MTS assay. **P < 0.01, *P < 0.05 (one‐way ANOVA). ns, not statistically significant difference. (G) Cell death analysis via PI staining followed by flow cytometry for INS-1 cells transfected with vector, WT Pbk, or mutant Pbk expression plasmids. ns, not statistically significant difference (one‐way ANOVA). (H) WB results for Pbk expression in PIME cells transfected with vector, WT Pbk, or mutant Pbk-expressing plasmids. (I) Cell growth curves of PIME cells transfected with vector, WT Pbk, or mutant Pbk expressing plasmids (n = 3). ***P < 0.001 (two‐way ANOVA, transfection construct and time are two categorical variables). ns, not statistically significant difference. (J) Cell growth of PIME cells transfected with vector, WT Pbk, or mutant Pbk expression plasmids was assessed by MTS assay. **P < 0.01, *P < 0.05 (one‐way ANOVA). ns, not statistically significant difference. (K) Cell death analysis via PI staining followed by flow cytometry for PIME cells transfected with vector, WT Pbk, or mutant Pbk expression plasmids. ns, not statistically significant difference (one‐way ANOVA).
Citation: Journal of Endocrinology 252, 2; 10.1530/JOE-21-0114
Antibodies used for Western blot, IF, and ChIP assays
Antibodies and oligoes used for Western blot, IF, and ChIP assays in this study.
| Reagent or Resource | Source | Identifier |
|---|---|---|
| Antibodies | ||
| Mouse monoclonal anti-Insulin | Cell Signaling Technology | Cat# 8138S |
| Mouse monoclonal anti-PBK | BD | Cat# 612170 |
| Rabbit polyclonal anti-PBK | Abcam | Cat# ab226923 |
| Rat monoclonal anti-BrdU | Abcam | Cat# ab6326 |
| Rabbit monoclonal anti-STAT5 | Cell Signaling Technology | Cat# ab94205 |
| Rabbit polyclonal anti-P-STAT5 | Cell Signaling Technology | Cat# ab9351 |
| Anti-POL-2 | Abcam | Cat# ab5131 |
| Rabbit polyclonal anti-Mouse IgG H&L | Abcam | Cat# ab46540 |
| Mouse monoclonal anti-bate actin | Sigma | Cat# A5441 |
| Goat Anti-Rabbit IgG (H + L)-HRP | BIO-Rad | Cat# 1706515 |
| Goat Anti-Mouse IgG (H+L)-HRP | BIO-Rad | Cat# 1721011 |
| Donkey anti-Rabbit IgG Cy5 | Jackson ImmunoResearch | Code:711-175-152 |
| Donkey anti-mouse IgG Cy3 | Jackson ImmunoResearch | Code:715-165-151 |
| Alexa Fluor 546 goat anti-rabbit IgG (H+L) | Life technologies | Cat# A11035 |
| Goat anti-Rabbit IgG-488 | ThermoFisher | Cat# A-11008 |
| Goat anti-mouse IgG-488 | ThermoFisher | Cat# A-11001 |
| Fedratinib (JAK inhibitor) | Selleck Chemicals | Cat# S2736 |
| STAT5 inhibitor | Sigma | Cat# 573108 |
| Oligonucleotides | ||
| mouse/Rat Pbk-F | This paper | TTGCTATGGAGTATGGAGGTG |
| mouse/Rat Pbk-R | This paper | GATACTTTAGCCCTCTTGCCA |
| Mouse actin-F | CTGTCCCTGTATGCCTCTG | |
| Mouse actin-R | ATGTCACGCACGATTTCC |
Statistical analysis
For all experiments, the number of biological replicates (n), measure of central tendency (e.g. average), error bars, and statistical analysis have been explained in the Figure legends. For each experiment where statistics were computed, we used at least n = 3 or more biological replicates. All statistically significant comparisons are indicated in the figures and corresponding legends. Data are presented as mean ± s.e.m. Unpaired two-tailed Student’s t-test is used to compare the means of two groups; comparisons of the means of more than two groups are performed using one-way or two-way ANOVA, according to the design, which had been detailed described in figure legends. We chose Tukey–Kramer test for post hoc tests. Statistical significance was indicated using GraphPad Prism6 (GraphPad Software) or Microsoft Excel (Microsoft) and considered significant at P < 0.05.
Results
Pbk is upregulated during pregnancy, and Pbk kinase activity is essential for β-cell proliferation during pregnancy
To determine whether the expression of Pbk is influenced by pregnancy in mice, we isolated pancreas from control and pregnant mice at GD15.5, with immunofluorescence (IF) staining showing that Pbk expression was observed in increased number of insulin positive islet cells from pregnant mice (Fig. 1A and B). Quantification of the percentage of insulin and Pbk double positive cells from islets showed a significant increase in pregnant mice (Fig. 1C). Moreover, to further evaluate the impact of Pbk on promoting proliferation on β-cells, we ectopically expressed WT Pbk or kinase dead mutant Pbk in INS-1 cells or PIME cells, a cell line derived from mouse islets (Yang et al. 2010), and Western blot showed the increased WT or mutant Pbk expression (Fig. 1D and H). Cell quantification and MTS assay results showed that ectopic expression of WT Pbk increased cell number compared to vector-treated cells, but ectopic expression of mutant Pbk failed to increase the cell number (Fig. 1E, F, G and I). The result of PI staining followed by flow cytometry for the cells was similar with no significant differences (Fig. 1G and K).
Together, these results suggest that upregulation of Pbk in β-cells of mice during pregnancy is crucial for increased cell proliferation.
Ablation of Pbk kinase activity by Pbk knock-in (Pbk-KI) led to impaired glucose tolerance in mice during pregnancy
We sought to further evaluate the potential impact of genetic mutation of Pbk in mice on β-cell proliferation in vivo. Mice bearing dysfunctional Pbk kinase mutant KI were generated by introducing KI of Pbk K64K65→AA mutation (Gaudet et al. 2000) (referred to as PbkKI/KI hereafter), using CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) technology, as reported in another manuscript in preparation (Ma et al. 2021).
Prior to pregnancy, there was no statistically significant difference in glucose tolerance test (GTT) and area under curve (AUC) between female WT and PbkKI/KI mice (n = 8) (Fig. 2A). And also there was no statistically significant difference in glucose-stimulated insulin secretion (GSIS) between PbkWT/WT non-pregnant mice and PbkKI/KI non-pregnant mice (n = 4) (Fig. 2B). In WT mice, the GT before and during pregnancy showed similar pattern, with no sign of the impaired GT (Fig. 2C). Notably, following pregnancy at GD 16.5, pregnant PbkKI/KI mice showed impaired GT as compared to PbkKI/KI non-pregnant mice or PbkWT/WT pregnant mice, with significantly increased AUC by ANOVA analysis (n = 4) and also lower insulin level of GSIS as compared to PbkWT/WT pregnant mice (Fig. 2C and D). To further investigate whether impaired glucose tolerance during pregnancy was correlated with insulin resistance caused by weight gain, we also monitored the change in body weight and insulin tolerance test (ITT). We found that both groups of pregnant mice showed similar body weight (Fig. 2E), ITT and AUC (Fig. 2F and G), without statistical difference. Together, these results suggest that Pbk kinase deactivation in mice led to impaired glucose tolerance during pregnancy and thus Pbk is important for adaptive maintenance of islet function during pregnancy.
Pbk kinase deactivation led to impaired glucose tolerance in mice during pregnancy. (A) Glucose tolerance tests (GTT) on control PbkWT/WT or PbkKI/KI mice were performed (glucose administered intraperitoneally at 2 g/kg of bodyweight), The GTT graph and area under curve (AUC) (A) were compared among the two groups of the mice using two-way ANOVA analysis (group and time are two categorical variables). PbkWT/WT and PbkKI/KI mice (n = 8), 8 weeks old for each group of mice were used. (B) Glucose-stimulated insulin secretion (GSIS) on PbkWT/WT and PbkKI/KI non-pregnant mice (n = 4) were performed. The mice were starved overnight prior to the test (16 h). Y-axis represents the ratio of insulin level at 15 min over insulin level at 0 min with glucose challenge. ns, not statistically significant difference (two-tailed Student’s t-test). (C) GTTs were performed on PbkWT/WT and PbkKI/KI non-pregnant (n = 4) and pregnant mice (n = 4) at GD15.5 during pregnancy. The GTT graph and AUC (C) were compared among the four groups of the mice using two-way ANOVA analysis (group and time are two categorical variables). (D) Glucose-stimulated insulin secretion (GSIS) on PbkWT/WT and PbkKI/KI pregnant mice (n =4) were performed. The mice were starved overnight prior to the test (16 h). Y-axis represents the ratio of insulin level at 15 min over insulin level at 0 min with glucose challenge. *P < 0.05 (two-tailed Student’s t-test). (E) Bodyweight of PbkWT/WT and PbkKI/KI pregnant mice (n = 4) at GD0.5 and GD15.5 during pregnancy. (F and G) Insulin tolerance test (ITT) (F) and AUC comparison of the ITT results (G) between the two groups of PbkWT/WT pregnant (n = 4) and PbkKI/KI pregnant (n = 4) mice at GD16.5 during pregnancy using two-way ANOVA analysis (group and time are two categorical variables). ***P < 0.001, **P < 0.01, *P < 0.05. ns, not statistically significant difference.
Citation: Journal of Endocrinology 252, 2; 10.1530/JOE-21-0114
Pbk kinase deactivation led to impaired glucose tolerance in mice during pregnancy. (A) Glucose tolerance tests (GTT) on control PbkWT/WT or PbkKI/KI mice were performed (glucose administered intraperitoneally at 2 g/kg of bodyweight), The GTT graph and area under curve (AUC) (A) were compared among the two groups of the mice using two-way ANOVA analysis (group and time are two categorical variables). PbkWT/WT and PbkKI/KI mice (n = 8), 8 weeks old for each group of mice were used. (B) Glucose-stimulated insulin secretion (GSIS) on PbkWT/WT and PbkKI/KI non-pregnant mice (n = 4) were performed. The mice were starved overnight prior to the test (16 h). Y-axis represents the ratio of insulin level at 15 min over insulin level at 0 min with glucose challenge. ns, not statistically significant difference (two-tailed Student’s t-test). (C) GTTs were performed on PbkWT/WT and PbkKI/KI non-pregnant (n = 4) and pregnant mice (n = 4) at GD15.5 during pregnancy. The GTT graph and AUC (C) were compared among the four groups of the mice using two-way ANOVA analysis (group and time are two categorical variables). (D) Glucose-stimulated insulin secretion (GSIS) on PbkWT/WT and PbkKI/KI pregnant mice (n =4) were performed. The mice were starved overnight prior to the test (16 h). Y-axis represents the ratio of insulin level at 15 min over insulin level at 0 min with glucose challenge. *P < 0.05 (two-tailed Student’s t-test). (E) Bodyweight of PbkWT/WT and PbkKI/KI pregnant mice (n = 4) at GD0.5 and GD15.5 during pregnancy. (F and G) Insulin tolerance test (ITT) (F) and AUC comparison of the ITT results (G) between the two groups of PbkWT/WT pregnant (n = 4) and PbkKI/KI pregnant (n = 4) mice at GD16.5 during pregnancy using two-way ANOVA analysis (group and time are two categorical variables). ***P < 0.001, **P < 0.01, *P < 0.05. ns, not statistically significant difference.
Citation: Journal of Endocrinology 252, 2; 10.1530/JOE-21-0114
Pbk kinase deactivation led to impaired glucose tolerance in mice during pregnancy. (A) Glucose tolerance tests (GTT) on control PbkWT/WT or PbkKI/KI mice were performed (glucose administered intraperitoneally at 2 g/kg of bodyweight), The GTT graph and area under curve (AUC) (A) were compared among the two groups of the mice using two-way ANOVA analysis (group and time are two categorical variables). PbkWT/WT and PbkKI/KI mice (n = 8), 8 weeks old for each group of mice were used. (B) Glucose-stimulated insulin secretion (GSIS) on PbkWT/WT and PbkKI/KI non-pregnant mice (n = 4) were performed. The mice were starved overnight prior to the test (16 h). Y-axis represents the ratio of insulin level at 15 min over insulin level at 0 min with glucose challenge. ns, not statistically significant difference (two-tailed Student’s t-test). (C) GTTs were performed on PbkWT/WT and PbkKI/KI non-pregnant (n = 4) and pregnant mice (n = 4) at GD15.5 during pregnancy. The GTT graph and AUC (C) were compared among the four groups of the mice using two-way ANOVA analysis (group and time are two categorical variables). (D) Glucose-stimulated insulin secretion (GSIS) on PbkWT/WT and PbkKI/KI pregnant mice (n =4) were performed. The mice were starved overnight prior to the test (16 h). Y-axis represents the ratio of insulin level at 15 min over insulin level at 0 min with glucose challenge. *P < 0.05 (two-tailed Student’s t-test). (E) Bodyweight of PbkWT/WT and PbkKI/KI pregnant mice (n = 4) at GD0.5 and GD15.5 during pregnancy. (F and G) Insulin tolerance test (ITT) (F) and AUC comparison of the ITT results (G) between the two groups of PbkWT/WT pregnant (n = 4) and PbkKI/KI pregnant (n = 4) mice at GD16.5 during pregnancy using two-way ANOVA analysis (group and time are two categorical variables). ***P < 0.001, **P < 0.01, *P < 0.05. ns, not statistically significant difference.
Citation: Journal of Endocrinology 252, 2; 10.1530/JOE-21-0114
Upregulation of Pbk in islets is critical for β-cell proliferation and increasing islet mass during pregnancy
To assess the potential role of Pbk in β-cell proliferation and islet mass in mice during pregnancy, we performed histological studies of pancreatic islets from both control and PbkKI/KI mice. To this end, we injected BrdU to the mice intraperitoneally 3 days prior to the sacrifice and collected the pancreata for the histological studies at GD17.5. IF staining for insulin and BrdU showed that pregnant WT Pbk mice had significantly increased β-cells with expression of BrdU, a marker of proliferative cells (Fig. 3A, B and E). Notably, PbkKI/KI mice partly reduced gestation-increased β-cell proliferation (Fig. 3C, D and E). In the PbkWT/WT group of mice, the rate of β-cell proliferation increased by almost 14.7-fold in pregnancy, as compared with the non-pregnant group (Fig. 3E, left two columns). In contrast, the rate of β-cell proliferation increased by only 6.9-fold in pregnancy in the PbkKI/KI group of mice (Fig. 3E, right two columns). Comparing the rate of induction of β-cell proliferation (BrdU uptake) by pregnancy between the control and the PbkKI/KI group of mice show that PbkKI/KI mice underwent 53.1% reduction in the induction of β-cell proliferation as compared to that in the control PbkWT/WT mice (Fig. 3F). Consistently, IF staining also showed that both WT pregnant mice and PbkKI/KI pregnant mice had increased β-cells with Pbk expression, without significant statistical difference, as both WT Pbk and Pbk-KI mutant Pbk loci remain controlled by the same endogenous promoter in the genome (Fig. 3G, H, I, J, K and L). These results demonstrate that Pbk expression was upregulated during pregnancy, and WT Pbk is required for gestation-mediated increase in β-cell proliferation.
Pbk kinase deactivation reduced β-cell proliferation in mice during pregnancy. (A, B, C and D) Representative images of double staining for insulin (green) and BrdU (red) in islets from GD16.5 PbkWT/WT and PbkKI/KI non-pregnant and pregnant mice (n = 4). Nuclei were labeled by DAPI (blue). Scale bar: 50 μm; (E) Quantification of BrdU positive β cells (four mice/group, ten islets for each mouse). The results are represented as mean ± s.e.m. ****P < 0.0001, ***P < 0.001, **P < 0.01 (one-way ANOVA). (F) Calculated relative folds of cell proliferation in pregnant and non-pregnant mice of PbkWT/WT and PbkKI/KI groups. Data are represented as mean ± s.e.m. **P < 0.01 (two-tailed Student’s t-test). (G, H, I and J) Representative images of double staining for insulin (green) and Pbk (red) in islets from GD 16.5 PbkWT/WT and PbkKI/KI non-pregnant and pregnant mice (n = 4). Nuclei were labeled by DAPI (blue). Scale bar: 50 μm.(K) Quantification of Pbk positive β-cells (four mice/group, ten islets for each mouse). Data are represented as mean ± s.e.m. ****P < 0.0001 (one-way ANOVA). (L) Calculated relative folds of Pbk upregulation in pregnant and non-pregnant mice of PbkWT/WT and PbkKI/KI groups. Data are represented as mean ± s.e.m. ns, not statistically significant difference (two-tailed Student’s t-test).
Citation: Journal of Endocrinology 252, 2; 10.1530/JOE-21-0114
Pbk kinase deactivation reduced β-cell proliferation in mice during pregnancy. (A, B, C and D) Representative images of double staining for insulin (green) and BrdU (red) in islets from GD16.5 PbkWT/WT and PbkKI/KI non-pregnant and pregnant mice (n = 4). Nuclei were labeled by DAPI (blue). Scale bar: 50 μm; (E) Quantification of BrdU positive β cells (four mice/group, ten islets for each mouse). The results are represented as mean ± s.e.m. ****P < 0.0001, ***P < 0.001, **P < 0.01 (one-way ANOVA). (F) Calculated relative folds of cell proliferation in pregnant and non-pregnant mice of PbkWT/WT and PbkKI/KI groups. Data are represented as mean ± s.e.m. **P < 0.01 (two-tailed Student’s t-test). (G, H, I and J) Representative images of double staining for insulin (green) and Pbk (red) in islets from GD 16.5 PbkWT/WT and PbkKI/KI non-pregnant and pregnant mice (n = 4). Nuclei were labeled by DAPI (blue). Scale bar: 50 μm.(K) Quantification of Pbk positive β-cells (four mice/group, ten islets for each mouse). Data are represented as mean ± s.e.m. ****P < 0.0001 (one-way ANOVA). (L) Calculated relative folds of Pbk upregulation in pregnant and non-pregnant mice of PbkWT/WT and PbkKI/KI groups. Data are represented as mean ± s.e.m. ns, not statistically significant difference (two-tailed Student’s t-test).
Citation: Journal of Endocrinology 252, 2; 10.1530/JOE-21-0114
Pbk kinase deactivation reduced β-cell proliferation in mice during pregnancy. (A, B, C and D) Representative images of double staining for insulin (green) and BrdU (red) in islets from GD16.5 PbkWT/WT and PbkKI/KI non-pregnant and pregnant mice (n = 4). Nuclei were labeled by DAPI (blue). Scale bar: 50 μm; (E) Quantification of BrdU positive β cells (four mice/group, ten islets for each mouse). The results are represented as mean ± s.e.m. ****P < 0.0001, ***P < 0.001, **P < 0.01 (one-way ANOVA). (F) Calculated relative folds of cell proliferation in pregnant and non-pregnant mice of PbkWT/WT and PbkKI/KI groups. Data are represented as mean ± s.e.m. **P < 0.01 (two-tailed Student’s t-test). (G, H, I and J) Representative images of double staining for insulin (green) and Pbk (red) in islets from GD 16.5 PbkWT/WT and PbkKI/KI non-pregnant and pregnant mice (n = 4). Nuclei were labeled by DAPI (blue). Scale bar: 50 μm.(K) Quantification of Pbk positive β-cells (four mice/group, ten islets for each mouse). Data are represented as mean ± s.e.m. ****P < 0.0001 (one-way ANOVA). (L) Calculated relative folds of Pbk upregulation in pregnant and non-pregnant mice of PbkWT/WT and PbkKI/KI groups. Data are represented as mean ± s.e.m. ns, not statistically significant difference (two-tailed Student’s t-test).
Citation: Journal of Endocrinology 252, 2; 10.1530/JOE-21-0114
Consistent with the result in β-cell proliferation, IF staining of pancreatic sections from WT Pbk pregnant mice showed significant increase in islet mass (Fig. 4A, B and E). IF staining of the pancreata showed that in the PbkWT/WT group of mice, β-cell mass increased by almost 1.88-fold in the pregnant group, as compared with the non-pregnant group. In contrast, the PbkKI/KI group showed that the islet mass increased by only 1.33-fold, a 29.1% reduction in the β-cell mass increase as compared to that from the WT PbkWT/WT mice (Fig. 4A, B, C, D, E and F). Together, these findings provide strong evidence that Pbk kinase activity is essential for gestation-mediated β-cell proliferation and increase in islet mass.
Pbk kinase deactivation reduced β-cell mass in mice during pregnancy. (A, B, C, and D) Representative whole-scan images of entire pancreas sections from GD16.5 PbkWT/WT and PbkKI/KI non-pregnant and pregnant mice used for β-cell area. Insulin immunofluorescence (red) and DAPI (blue) (scale bar, 2 mm). (E) Calculated β-cell mass in GD16.5 PbkWT/WT and PbkKI/KI non-pregnant and pregnant mice (n = 4). Data are represented as mean ± s.e.m. ****P < 0.0001, **P < 0.01 (one-way ANOVA). (F) Calculated relative folds of β-cell mass increasing in pregnant and non-pregnant mice of PbkWT/WT and PbkKI/KI groups. Data are represented as mean ± s.e.m. ***P < 0.001 (two-tailed Student’s t-test).
Citation: Journal of Endocrinology 252, 2; 10.1530/JOE-21-0114
Pbk kinase deactivation reduced β-cell mass in mice during pregnancy. (A, B, C, and D) Representative whole-scan images of entire pancreas sections from GD16.5 PbkWT/WT and PbkKI/KI non-pregnant and pregnant mice used for β-cell area. Insulin immunofluorescence (red) and DAPI (blue) (scale bar, 2 mm). (E) Calculated β-cell mass in GD16.5 PbkWT/WT and PbkKI/KI non-pregnant and pregnant mice (n = 4). Data are represented as mean ± s.e.m. ****P < 0.0001, **P < 0.01 (one-way ANOVA). (F) Calculated relative folds of β-cell mass increasing in pregnant and non-pregnant mice of PbkWT/WT and PbkKI/KI groups. Data are represented as mean ± s.e.m. ***P < 0.001 (two-tailed Student’s t-test).
Citation: Journal of Endocrinology 252, 2; 10.1530/JOE-21-0114
Pbk kinase deactivation reduced β-cell mass in mice during pregnancy. (A, B, C, and D) Representative whole-scan images of entire pancreas sections from GD16.5 PbkWT/WT and PbkKI/KI non-pregnant and pregnant mice used for β-cell area. Insulin immunofluorescence (red) and DAPI (blue) (scale bar, 2 mm). (E) Calculated β-cell mass in GD16.5 PbkWT/WT and PbkKI/KI non-pregnant and pregnant mice (n = 4). Data are represented as mean ± s.e.m. ****P < 0.0001, **P < 0.01 (one-way ANOVA). (F) Calculated relative folds of β-cell mass increasing in pregnant and non-pregnant mice of PbkWT/WT and PbkKI/KI groups. Data are represented as mean ± s.e.m. ***P < 0.001 (two-tailed Student’s t-test).
Citation: Journal of Endocrinology 252, 2; 10.1530/JOE-21-0114
Prolactin induces Pbk expression through regulating the JAK-STAT pathway
In order to understand how pregnancy upregulates Pbk expression, we sought to investigate whether hormones that are upregulated during pregnancy affect Pbk expression. To this end, we treated β-cells with prolactin, estradiol, or progesterone, which are all hormones that fluctuate and play important roles during pregnancy (Khan-Dawood & Dawood 1984, Moon et al. 2020, Monteiro et al. 2021). Notably, we observed a robust increase in the protein and mRNA levels of Pbk by prolactin, in a dose-dependent manner in INS-1 cells (Fig. 5A and B) and PIME cells (Fig. 5C and D). However, estradiol and progesterone failed to induce Pbk expression in protein (Supplementary Fig. 1A and B, see section on supplementary materials given at the end of this article) and mRNA levels (data not shown). Prolactin functions through binding its cell surface receptor and activating Jak kinase, which then phosphorylates STAT3 and STAT5, to induce transcription of genes that are important for cell proliferation and differentiation (Brelje et al. 2004). As such, we sought to investigate whether prolactin induces Pbk expression and β-cell compensatory proliferation during pregnancy through the JAK-STAT pathway. Using prolactin receptor (Prlr receptor) shRNAs, we established cell lines with reduced expression levels of the prolactin receptor (Prlr) (Fig. 6A). As expected, treatment of the vector control cells with prolactin upregulated the level of p-STAT5 (Fig. 6A, lane 2 vs lane 1), the JAK phosphorylated and active form of STAT5, as well as the protein level of Pbk (Fig. 6A, lane 2 vs 1). Notably, knockdown of prolactin receptor Prlr abolished prolactin-induced STAT5 phosphorylation (Fig. 6A, lanes 4, 6 vs 3, 5), as well as induction of Pbk protein level (Fig. 6A, lanes 4, 6 vs 3, 5), albeit still with background Pbk protein expression. Consistently, qRT-PCR also showed that Prlr knockdown blocked the increase in Pbk mRNA expected by prolactin administration (Fig. 6B), even though the background Pbk mRNA level remained detectable. Together, these results suggest that prolactin signaling definitively induces STAT5 phosphorylation and Pbk expression at the mRNA and protein level through activating Prlr, and a background level of Pbk expression independent prolactin signaling exists.
Prolactin induced Pbk expression in INS-1 and PIME cells. (A and B) WB results (A) and qPCR results (B) for detecting Pbk expression in INS-1 cells treated with different concentrations of prolactin for 24 h. (C and D) WB results (C) and qPCR results (D) for detecting Pbk expression in PIME cells treated with different prolactin concentrations for 24 h. Relative protein levels of Pbk were normalized to β-actin (n = 3). ****P < 0.0001, ***P < 0.001, **P < 0.01 (one-way ANOVA).
Citation: Journal of Endocrinology 252, 2; 10.1530/JOE-21-0114
Prolactin induced Pbk expression in INS-1 and PIME cells. (A and B) WB results (A) and qPCR results (B) for detecting Pbk expression in INS-1 cells treated with different concentrations of prolactin for 24 h. (C and D) WB results (C) and qPCR results (D) for detecting Pbk expression in PIME cells treated with different prolactin concentrations for 24 h. Relative protein levels of Pbk were normalized to β-actin (n = 3). ****P < 0.0001, ***P < 0.001, **P < 0.01 (one-way ANOVA).
Citation: Journal of Endocrinology 252, 2; 10.1530/JOE-21-0114
Prolactin induced Pbk expression in INS-1 and PIME cells. (A and B) WB results (A) and qPCR results (B) for detecting Pbk expression in INS-1 cells treated with different concentrations of prolactin for 24 h. (C and D) WB results (C) and qPCR results (D) for detecting Pbk expression in PIME cells treated with different prolactin concentrations for 24 h. Relative protein levels of Pbk were normalized to β-actin (n = 3). ****P < 0.0001, ***P < 0.001, **P < 0.01 (one-way ANOVA).
Citation: Journal of Endocrinology 252, 2; 10.1530/JOE-21-0114
Prolactin induced Pbk expression through JAK-STAT pathway. (A and B) WB results from PIME cells stably transfected with control vector or prolactin receptor (prlr) shRNA1 or shRNA2, followed by treatment with or without 1 ng/mL prolactin for 30 min, and detecting STAT5 and p-STAT5 with the specific antibodies. For detecting prlr and Pbk proteins, the cells were treated for 24 h and then detected for the prlr and Pbk proteins by Western blot. Relative protein levels of Pbk were normalized to β-actin (n = 3) (A). qPCR results for detecting Pbk expression from the cells treated with 1 ng/mL prolactin for 24 h (B). ***P < 0.001, *P < 0.05 (one-way ANOVA). (C and D) WB results for PIME cells treated with or without 1 ng/mL prolactin in the absence or presence of 2.5 µM fedratinib for 30 min for detecting STAT5 and p-STAT5 or for 24 h for detecting Pbk expression. Relative protein levels of Pbk were normalized to β-actin (n = 3) (C). qPCR results for detecting Pbk expression (D). ***P < 0.001, **P < 0.01 (one-way ANOVA). (E and F) WB results for PIME cells treated with or without 1 ng/mL prolactin in the absence or presence of 30 μM STAT5 inhibitor for 30 min for detecting STAT5 and p-STAT5 or for 24 h to detect Pbk expression. Relative protein levels of Pbk were normalized to β-actin (n = 3) (E). qRT-PCR results for Pbk expression (F). ***P < 0.001, *P < 0.05 (one-way ANOVA).
Citation: Journal of Endocrinology 252, 2; 10.1530/JOE-21-0114
Prolactin induced Pbk expression through JAK-STAT pathway. (A and B) WB results from PIME cells stably transfected with control vector or prolactin receptor (prlr) shRNA1 or shRNA2, followed by treatment with or without 1 ng/mL prolactin for 30 min, and detecting STAT5 and p-STAT5 with the specific antibodies. For detecting prlr and Pbk proteins, the cells were treated for 24 h and then detected for the prlr and Pbk proteins by Western blot. Relative protein levels of Pbk were normalized to β-actin (n = 3) (A). qPCR results for detecting Pbk expression from the cells treated with 1 ng/mL prolactin for 24 h (B). ***P < 0.001, *P < 0.05 (one-way ANOVA). (C and D) WB results for PIME cells treated with or without 1 ng/mL prolactin in the absence or presence of 2.5 µM fedratinib for 30 min for detecting STAT5 and p-STAT5 or for 24 h for detecting Pbk expression. Relative protein levels of Pbk were normalized to β-actin (n = 3) (C). qPCR results for detecting Pbk expression (D). ***P < 0.001, **P < 0.01 (one-way ANOVA). (E and F) WB results for PIME cells treated with or without 1 ng/mL prolactin in the absence or presence of 30 μM STAT5 inhibitor for 30 min for detecting STAT5 and p-STAT5 or for 24 h to detect Pbk expression. Relative protein levels of Pbk were normalized to β-actin (n = 3) (E). qRT-PCR results for Pbk expression (F). ***P < 0.001, *P < 0.05 (one-way ANOVA).
Citation: Journal of Endocrinology 252, 2; 10.1530/JOE-21-0114
Prolactin induced Pbk expression through JAK-STAT pathway. (A and B) WB results from PIME cells stably transfected with control vector or prolactin receptor (prlr) shRNA1 or shRNA2, followed by treatment with or without 1 ng/mL prolactin for 30 min, and detecting STAT5 and p-STAT5 with the specific antibodies. For detecting prlr and Pbk proteins, the cells were treated for 24 h and then detected for the prlr and Pbk proteins by Western blot. Relative protein levels of Pbk were normalized to β-actin (n = 3) (A). qPCR results for detecting Pbk expression from the cells treated with 1 ng/mL prolactin for 24 h (B). ***P < 0.001, *P < 0.05 (one-way ANOVA). (C and D) WB results for PIME cells treated with or without 1 ng/mL prolactin in the absence or presence of 2.5 µM fedratinib for 30 min for detecting STAT5 and p-STAT5 or for 24 h for detecting Pbk expression. Relative protein levels of Pbk were normalized to β-actin (n = 3) (C). qPCR results for detecting Pbk expression (D). ***P < 0.001, **P < 0.01 (one-way ANOVA). (E and F) WB results for PIME cells treated with or without 1 ng/mL prolactin in the absence or presence of 30 μM STAT5 inhibitor for 30 min for detecting STAT5 and p-STAT5 or for 24 h to detect Pbk expression. Relative protein levels of Pbk were normalized to β-actin (n = 3) (E). qRT-PCR results for Pbk expression (F). ***P < 0.001, *P < 0.05 (one-way ANOVA).
Citation: Journal of Endocrinology 252, 2; 10.1530/JOE-21-0114
To further determine whether prolactin-induced Pbk expression occurred through the JAK-STAT pathway, we treated PIME cells with either a JAK inhibitor (Jin et al. 2018) or STAT5 inhibitor, which blocks STAT5 DNA binding activity (Muller et al. 2008), followed by Western blot analysis of p-STAT5 and Pbk. The results showed that treatment with prolactin increased the level of p-STAT5 and Pbk (Fig. 6C, lane 2 vs 1). Importantly, addition of JAK inhibitor Fedratinib (Jin et al. 2018) blocked the prolactin-induced upregulation of p-STAT5 and Pbk at protein level (Fig. 6C, lane 4 vs 3) as well as at the Pbk mRNA level (Fig. 6D). Consistently, treatment of PIME cells with a STAT5 inhibitor also blocked the upregulation of Pbk expression influenced by prolactin at protein level (Fig. 6E) and the mRNA level (Fig. 6F). Together, these results indicate that prolactin pathway activation induces Pbk expression through the JAK-STAT pathway.
Prolactin signaling enhances the recruitment of STAT5 and RNA polymerase II to the Pbk promoter
The above experimental results showed that the JAK-STAT pathway is crucial for upregulation of Pbk expression influenced by prolactin, but the mechanism of this upregulation remains unclear. We sought to determine whether there were STAT5 binding sites at the Pbk locus. Notably, prior work (Soldaini et al. 2000) predicted a potential STAT5 binding site (TTCCAAGAA, SBS) at the Pbk locus in mice (Fig. 7A). We designed two different pairs of primers near this binding site to use in chromatin immunoprecipitation (ChIP) assays and performed additional CHIP assay around the Pbk promoter sequence that does not contain the predicted Stat5 binding site as a control (Fig. 7A). PIME cells were cultured with or without treatment with prolactin, followed by ChIP assay. ChIP assay showed that amplicons 0 location in Fig. 7A and B did not detect substantial difference in the binding of STAT5, p-STAT5, and RNA polymerase II level at the Pbk locus between the prolactin treated PIME cell and the control cells. The results indicate that prolactin treatment increases STAT5 and p-STAT5 binding at the Pbk promoter, as well as RNA polymerase II, consistent with increasing Pbk transcription (Fig. 7C). Similar results were also observed at a different location of the Pbk promoter (Fig. 7D). Collectively, these results indicate that prolactin binds to its cell surface receptor on β cells, induces phosphorylation of STAT5, which then enters the nucleus, binds to the Pbk promoter, upregulates Pbk transcription, and ultimately increase β-cell proliferation (Fig. 7E).
Prolactin treatment enhanced the enrichment of STAT5 at the Pbk promoter. (A) The predicted STAT5 binding site at the Pbk gene promoter via software PROMO3.0, and the diagram depicting the primer pairs to amplify the promoter sequences of the Pbk promoter with amplicons 1 and 2, while amplicon 0 that does not contain the predicted Stat5 binding site was used as a negative control. (B, C and D) The results of the ChIP assay from PIME cells treated with or without 1 ng/mL prolactin, amplified with amplicon 0 primers (B), amplicon 1 primers (C), or amplicon 2 primers (D). The prolactin-treated PIME cell and the control cells were subjected to ChIP assay to detect the binding of STAT5, p-STAT5, and RNA polymerase II level at the Pbk locus using three different amplicons. The results were repeated three times. (E) A working model for prolactin enhanced Pbk expression in β-cells though JAK-STAT pathway during mouse pregnancy. *P < 0.05 (two-tailed Student’s t-test).
Citation: Journal of Endocrinology 252, 2; 10.1530/JOE-21-0114
Prolactin treatment enhanced the enrichment of STAT5 at the Pbk promoter. (A) The predicted STAT5 binding site at the Pbk gene promoter via software PROMO3.0, and the diagram depicting the primer pairs to amplify the promoter sequences of the Pbk promoter with amplicons 1 and 2, while amplicon 0 that does not contain the predicted Stat5 binding site was used as a negative control. (B, C and D) The results of the ChIP assay from PIME cells treated with or without 1 ng/mL prolactin, amplified with amplicon 0 primers (B), amplicon 1 primers (C), or amplicon 2 primers (D). The prolactin-treated PIME cell and the control cells were subjected to ChIP assay to detect the binding of STAT5, p-STAT5, and RNA polymerase II level at the Pbk locus using three different amplicons. The results were repeated three times. (E) A working model for prolactin enhanced Pbk expression in β-cells though JAK-STAT pathway during mouse pregnancy. *P < 0.05 (two-tailed Student’s t-test).
Citation: Journal of Endocrinology 252, 2; 10.1530/JOE-21-0114
Prolactin treatment enhanced the enrichment of STAT5 at the Pbk promoter. (A) The predicted STAT5 binding site at the Pbk gene promoter via software PROMO3.0, and the diagram depicting the primer pairs to amplify the promoter sequences of the Pbk promoter with amplicons 1 and 2, while amplicon 0 that does not contain the predicted Stat5 binding site was used as a negative control. (B, C and D) The results of the ChIP assay from PIME cells treated with or without 1 ng/mL prolactin, amplified with amplicon 0 primers (B), amplicon 1 primers (C), or amplicon 2 primers (D). The prolactin-treated PIME cell and the control cells were subjected to ChIP assay to detect the binding of STAT5, p-STAT5, and RNA polymerase II level at the Pbk locus using three different amplicons. The results were repeated three times. (E) A working model for prolactin enhanced Pbk expression in β-cells though JAK-STAT pathway during mouse pregnancy. *P < 0.05 (two-tailed Student’s t-test).
Citation: Journal of Endocrinology 252, 2; 10.1530/JOE-21-0114
Discussion
GDM occurs during pregnancy with impaired glucose tolerance. Multiple factors, including maternal insulin resistance (Catalano et al. 1991, Nguyen-Ngo et al. 2019), β-cell insulin secretion, and β-cell proliferation, contribute to the development of GDM. During pregnancy, β-cells proliferate and regenerate through from hypertrophic precursor cells, accompanied by a temporary decrease in death to achieve a compensatory increase in the number of the cells (Butler et al. 2010, Ernst et al. 2011, Bonner-Weir et al. 2012). It was reported that inactivation of prolactin receptor gene in mice contributes to the development of GDM (Banerjee et al. 2016); however, it was not clear how the prolactin signaling pathway regulates pro-proliferative genes and β-cell proliferation during pregnancy.
PDZ binding kinase (Pbk) is a serine/threonine kinase related to the mitogen-activated protein kinase (MAPK) family. Pbk is mainly expressed at relatively high levels in the reproductive organs of adult mice (Abe et al. 2000). In our other research, we find that Pbk is induced in islets by high-fat diet (HFD) conditions in mice and human islets (Ma et al. 2021).There fore, this report shows that Pbk is expressed in human pancreatic islets. This finding is consistent with others’ previous observation on upregulation of Pbk expression in human islets with loss-of-function MEN1 mutation (Jiang et al. 2014). It acts as an important nexus for multiple oncogenic signaling pathways, including c-Jun p38, p53, ERK1/2, ETV4-uPAR, and c-Jun N-terminal kinase 1, 2, and 3 (JNK1/2/3) signaling pathways (Gaudet et al. 2000, Hu et al. 2010, Gao et al. 2019, Yang et al. 2019). It has been reported that Pbk plays a major role in mitotic phosphorylation, regulation of DNA damage repair, tumorigenesis, and therapeutic resistance through various protein phosphorylation reactions (Liu et al. 2015, Stauffer et al. 2017). Excessive activation of Pbk contributes to tumor proliferation, invasion, as well as treatment failure in a variety of tumor types (Dou et al. 2015, Yang et al. 2016).
Previous research has shown that Pbk was upregulated during pregnancy in mice (Uesato et al. 2018), but there is still no data to show the specific mechanism of prolactin-mediated regulation of Pbk in the adaptive proliferation of β-cells during pregnancy. Our manuscript was the first time to show the link between prolactin signaling and Pbk expression, which was important for β-cell proliferation during pregnancy. However, the physiological function and role of Pbk in β-cell proliferation during pregnancy remain underexplored. To ensure kinase function of Pbk in regulating β-cell proliferation during pregnancy, we generated dysfunctional Pbk kinase mutant KI mice by introducing KI of Pbk K64K65→AA mutation. In contrast, Pbk K64K65→AA mutant Pbk failed to induce cell proliferation, highlighting the crucial role of its kinase enzyme activity in promoting cell proliferation (Gaudet et al. 2000). We generated Pbk K64K65→AA Pbk kinase mutant KI mice through CRISPR/Cas9-mediated genome editing (Ma et al. 2021). In brief, PbkKI/KI promoted development of impaired glucose tolerance (IGT) only in male mice, at least partly by impairing pancreatic β-cell proliferation. The establishment of this mouse model has laid a foundation for further examining the potential impact of PbkKI /KI on the development of GDM (Ma et al. 2021).
We found that the Pbk mutation rendered the mice prone to the development of GDM and reduced proliferation of the β-cells in islets of the mice. Consistent with these findings, other reports show that the expression of Ccna2 and Ccnb1 in murine pancreatic islets increased concomitant with Pbk overexpression during pregnancy (Kim et al. 2010, Uesato et al. 2018). Upregulation of Ccna2 can enhance the proliferation of β-cells, so Ccna2 is a possible downstream target of Pbk that promotes the proliferation of β-cells (Song et al. 2008). And in our previous study, we also found Pbk directly phosphorylated Erk in vitro kinase assay. However, the correlation between Pbk-drived enhanced Erk phosphorylation and beta-cell proliferation needs to be further investigated. Together, our studies uncovered the critical role of Pbk in enhancing β proliferation during pregnancy. However, our findings do not rule out that PbkKI/KI may also affect other effects beyond β-cell proliferation, such as insulin secretion.
Genetic and cell biology studies suggest that prolactin receptor (PRLR) signaling is a crucial regulator of β-cell expansion (Brelje et al. 1989, Vasavada et al. 2000, Freemark et al. 2002). PRLR signaling involves multiple effectors, including signal transducer and activator of transcription 5 (STAT5), phosphatidylinositol 3-kinase (PI3K)-AKT, and MAPK-extracellular regulated protein kinase (ERK) pathways. Although STAT5 is considered a principal mediator of PRLR signaling, other signal transduction pathways are also critical for gestational β-cell adaptation. It was previously unclear whether there is any link between prolactin signaling and Pbk expression.
In order to identify the factors that affect Pbk expression and the proliferation of β-cells during pregnancy, we examined the potential impact of hormones that change significantly during pregnancy. Certain hormones, such as prolactin, can stimulate β-cell proliferation during pregnancy (Nielsen et al. 1992), but the detailed mechanism is not clear. In addition, the high concentration of estrogen in women can also promote the proliferation of β-cells (Le May et al. 2006). In our vitro experiments, we added different hormones to cultured cell lines with different concentrations for various period of times, to detect Pbk expression. But in our system, we only find that prolactin clearly upregulated Pbk expression at mRNA and protein levels.
Estrogen signaling was reported to promote β-cell proliferation. For instance, estrogen promotes β-cell proliferation in a mouse model of total ovariectomy and pancreatectomy (Choi et al. 2005). In addition, treatment with selective estrogen receptor β agonists can increase the number of BrdU-positive cells in mouse pancreatic islets. Mice with pancreas-specific deletion of Foxm1 not only display profound GDM but also exhibit pregnancy defects in β-cell mass that likely reflect Foxm1 roles in physiological β-cell proliferation (Zhang et al. 2006, 2010). Moreover, estradiol could induce upregulation of Pbk in human beta cell and MIN6 cell (Uesato et al. 2018). But this phenomenon couldn’t be seen in PIME cells and INS-1 cells. We guessed that the different type of cells is the possible reason for failure induction of Pbk by estradiol.
In the previous studies, it was reported that prolactin level in second trimester in mice is about 100–250 ng/mL (Phillipps et al. 2020) and others reported culturing cells with medium containing prolactin (200 ng/mL, recombinant rat prolactin) for 24 h (Zhao et al. 2019). However, in our culture system, a dose curve studies showed that 1–4 ng/mL of prolactin has already reached maximum in upregulating Pbk in both INS-1 and PIME cells (Fig. 5A and C, lane 5). It is possible that in the culture system, a lower concentration of prolactin below the physiological level of prolactin-induced Pbk can result from at least a couple of factors. First, different cell types in culture may have different sensitivity to prolactin induction. Secondly, the culture system with the fetal bovine serum may contain modulators of the prolactin signaling. Nevertheless, the prolactin-induced upregulation of Pbk is dependent on expression of prolactin receptor (Fig. 6A), as prolactin knockdown reduced prolactin-induced Pbk expression. Consistently, inhibiting activation of STAT5, a downstream effector of prolactin, also blocks prolactin-induced upregulation of Pbk mRNA (Fig. 6D).
In previous researches, they provided the first prospective evidence of a positive association between prolactin levels in early pregnancy and GDM risk (Li et al. 2020) and low prolactin levels during pregnancy were associated with higher HbA1c and risk of GDM (Overgaard et al. 2020). Together with that, we can find that prolactin level plays different important roles in different stages of pregnancy. It may even become a predictor of gestational diabetes. It was previously unclear how precisely prolactin signaling upregulates β-cell proliferation. A prior study of conventional PRLR knockout mice identified glucose intolerance, reduced body weight, and reduced β-cell mass in adult mice of both sexes. In our study, we firstly found that prolactin could upregulate p-STAT5 and Pbk in protein and mRNA level, but when we knocked down prolactin receptor (shRNA 1 and 2), the impact of prolactin stimulation blocked (Fig. 6A and B), highlighting the crucial prolactin/receptor signaling in upregulating Pbk expression. Supporting this interpretation, treating PIME cells with the JAK inhibitor and STAT5 inhibitor, also blocked the upregulation of Pbk expression at protein and mRNA level (Fig. 6C, D, E and F), demonstrating the essential role of the JAK-STAT pathway in prolactin-induced Pbk expression in β-cells during pregnancy. From the ChIP assay data, prolactin treatment enhanced the binding of STAT5 and p-STAT5 at the Pbk promoter, as well as RNA polymerase II, thus explaining the increased Pbk transcript levels at least partially at the transcriptional level (Fig. 7C and D). Collectively, these results suggest that STAT5 was able to bind to the Pbk locus and prolactin upregulated Pbk expression in transcription level.
In summary, first, we demonstrated that the expression of protein kinase Pbk was upregulated during pregnancy and Pbk is required for optimal β-cell proliferations. Secondly, we found that Pbk kinase activity is essential for β-cell adaptive proliferation during pregnancy and amelioration of gestational diabetes, as Pbk kinase deactivation reduced adaptive β-cell proliferation and mass, highlighting the critical role of Pbk in regulating gestational diabetes. Thirdly, we uncovered that prolactin induced Pbk expression through activating JAK-STAT pathway, and STAT5 binds to the Pbk locus to activate its transcription. Considered together, the current studies lead to a new concept that prolactin/JAK-STAT/Pbk acts as a key pathway of regulating β-cell proliferation during pregnancy (Fig. 7E), providing novel insights into developing novel therapies or prevention of gestational diabetes.
Supplementary materials
This is linked to the online version of the paper at https://doi.org/10.1530/JOE-21-0114.
Declaration of interest
The authors declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported.
Funding
This work was supported by Sanofi Innovation Award (iAward), 2019.
Author contribution statement
Y C, J M, and X Hua conceived and designed the studies, and performed the analysis and interpretation of the data, Y C performed majority of the experiments, and J M generated the Pbk KI mice. J M, X H, K B, C A, T H, S L, Z F, G X, Y W, and B K performed parts of the experiments or provided experimental inputs. C T performed bioinformatic analysis. X Z analyzed and interpreted part of the results. Y C and X Hua wrote the manuscript and all other authors revised it. All authors approved the final version of the paper.
Acknowledgements
The authors appreciate the assistance in the processing of the samples for histological studies by the Molecular Pathology & Imaging Core at University of Pennsylvania, in isolation of mouse islets by Pancreatic Islet Cell Biology Core at University of Pennsylvania, and generation of gene mutant KI mice at CRISPR/Cas9 Mouse Targeting Core and Transgenic and Chimeric Mouse Facility at University of Pennsylvania.
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