- Journal Details
- Format
- Journal
- eISSN
- 2544-3577
- First Published
- 01 Oct 2009
- Publication timeframe
- 4 times per year
- Languages
- English
The ovarian follicle consists of different types of cells, such as of oocytes (OCs), theca cells, ovarian surface epithelial cells and granulosa cells (GCs). GCs not only are fundamental for folliculogenesis and oogenesis, but they are also involved in cell communication. Releasing exosomes, small vesicles secreting miRNAs, and forming gap-junctions, they exchange nutrients and metabolites with OCs. The bidirectional stimulation allowed by gap-junctions promotes communication and reciprocal maturation stimulation between OCs and GCs, enhancing folliculogenesis and oogenesis [1].
Ovarian follicular cells show stem-like potential as they show changes in phenotype during long-term
The follicular epithelium is much more dynamic than the epithelium in the rest of the body. The follicular epithelium expands as the follicle grows. The number of layers of granulosa, forming the follicular epithelium, grow around the oocyte. Subsequently, the follicular epithelium expands laterally. However, the understanding of the follicular epithelial dynamics, which may disrupt if the follicle becomes atretic, remains poorly understood [6].
The endoderm is one of the three main germ layers and, after gastrulation, it primarily gives rise to the respiratory and digestive tracts together with being part of many glands, including thyroid, thymus, pancreas, and liver [7]. It is hypothesized that
The present study reports the transcriptomic profile of porcine GCs during their short-primary culture during 168 h. The main goal of presented study has been identify genes group response for processes associated with epithelium and endoderm development.
The material for research were isolated post-mortem from 40 mature gilts, which whose median age was 170 days and body weight 98 kg. After cutting the abdominal wall in the linea alba, the reproductive system was removed along with the digestive tract. The ovaries were severed together with a large fragment of broad ligament of uterus and transported to the laboratory at 38ºC in 0.9% NaCl within 30 min. In the laboratory, each ovary was removed from the ovarian bursa which was deep and voluminous.. The ovaries were ovoid in shape with a median length of 4,4 cm. Outer surface was coarse lumpy as mulberry fruit. The appearance of the outer surface of the ovaries was determined by ovarian follicles located in the parenchymatous zone.
Ovaries (n=80) after isolation, were incubated 15 min. in 38ºC in 0.9% NaCl. Thereafter, follicular fluid (FF) has been obtained from single preovulatory large follicles (diameter estimated greater than 5 mm (n=320)). All follicle have been punctured using sterile 20-G needle and syringe. Cumulus-oocyte complexes (COCs) were recovered and discarded. The follicular fluid with granulosa cells were used in research next step. FF with granulosa cells were centrifuge in 250 rpm (10 min, RT). After supernatant discarded, pellet were incubated 10 min. with collagenase type II (1mg/ml) (Invitrogen, USA). Cells pellet after centrifugation (RT, 250×g, 10 min.) has been suspend in culture medium. Culture medium consisted of Dulbecco's Modified Eagle's Medium (DMEM, Sigma-Aldrich, USA), 10% fetal bovine serum (FBS) (Sigma-Aldrich, USA), 200 mM L-glutamine (Invitrogen, USA), 10 mg/ml gentamycin (Invitrogen, USA), 10,000 units/ml penicillin and 10,000 μg/ml streptomycin (Invitrogen, USA). Cells were cultivated at 38.0°C under aerobic conditions (5% CO2). When confluence were more than 90%, cells were detached with 0.05% trypsin-EDTA (Invitrogen, USA) for 3–5 min. After them, cells have been passaging.
Cells in 4 time point of cell culture: 0h, 48h 96h, 144h were detached from cultures using 1x Trypsin solution Sigma-Aldrich Co., St. Louis, MO, USA). After centrifugation cells pellet was resuspend in TRI Reagent (Sigma-Aldrich Co., St. Louis, MO, USA). Samples have been stored in −80°C.Total RNA have been isolated according Chomczyński-Sacchi protocol [8].
The total amount of RNA have been evaluated based on optical density at 260 nm. Purity has been determined using 260/280 nm absorption ratio (NanoDrop 2000 spectrophotometer, Thermo-Fisher Scientific, Waltham, MA, USA). Only samples with RNA concentration over 500 ng and 260/280 absorption ratio higher than 1.8 were used in further studies (microarrays and RT-qPCR).
Briefly cDNA was subjected from Total RNA (100ng) (Ambion® WT Expression Kit). Obtained cDNA was biotin labeled and fragmentated by Affymetrix GeneChip® WT Terminal Labeling and Hybridization (Affymetrix). Biotin-labeled fragments of cDNA (5.5 μg) were hybridized to Affymetrix® Porcine Gene 1.1 ST Array Strip (48°C/20 h). Then, microarrays were washed and stained according to the technical protocol using Affymetrix GeneAtlas Fluidics Station. Subsequently the array strips were scanned by Imaging Station of GeneAtlas System. The preliminary analysis of the scanned chips was performed using Affymetrix GeneAtlasTM Operating Software. The quality of gene expression data was checked according to quality control criteria provided by the software. Obtained CEL files were imported into downstream data analysis software. All of presented analyses and graphs were performed by Bioconductor and R programming language. Each CEL file was merged with a description file. In order to correct background, normalize and summarize results, we used Robust Multiarray Averaging (RMA) algorithm.
Statistical significance of analyzed genes was performed by moderated t-statistics from the empirical Bayes method. Obtained p value was corrected for multiple comparisons using the Benjamini and Hochberg's false discovery rate. The selection of significantly changed gene expression was based on p-value beneath 0.05 and expression fold higher than 2. Differentially expressed genes were subjected to the selection of genes involved in regulation of granulosa cells differentiation towards endodermal and epithelial tissues. Differentially expressed gene list were uploaded to DAVID software (Database for Annotation, Visualization and Integrated Discovery), where “developmental process”, “cellular developmental process”, “regulation of cell differentiation”, “epithelium migration”, “epithelial cell proliferation”, “epithelial cell migration”, “epithelial cell differentiation”, “epithelial cell development”, “endodermal cell differentiation”, “endoderm formation”, “endoderm development” and “epithelium development” GO BP terms were obtained. Expression data of these genes were subjected to hierarchical clustering procedure and presented as a heatmap graph. Detailed analysis of genes belonging to selected GO BP terms were presented as plots using “GOplot” library [9].
Moreover, the interactions between proteins coded by selected genes and genes itself were investigated by STRING10 software (Search Tool for the Retrieval of Interacting Genes). STRING database contains information of protein/gene interactions, including experimental data, computational prediction methods and public text collections. STRING database engine provided us molecular interaction network formed between interested genes. Searching criteria based on co-occurrences of genes/proteins in scientific texts (textmining), coexpression and experimentally observed interactions.
Finally the functional interaction between genes that belongs to the chosen GO BP terms were investigated by REACTOME FIViz application to the Cytoscape 3.6.0 software. The Reactome FIViz app is designed to find pathways and network patterns related to cancer and other types of diseases. This app accesses the pathways stored in the Reactome database, allowing to do pathway enrichment analysis for a set of genes, visualize hit pathways using manually laid-out pathway diagrams directly in Cytoscape, and investigate functional relationships among genes in hit pathways. The app can also access the Reactome Functional Interaction (FI) network, a highly reliable, manually curated pathway-based protein functional interaction network covering over 60% of human proteins.
Six randomly selected downregulated genes belonging to selected ontological groups were validated (
The 6 most downregulated genes involved in regulation of granulosa cells differentiation towards endodermal and epithelial tissues were validated using RT-qPCR, 168h/0h
| integral membrane protein 2A | ITM2A | -8.85 | <0.05 |
| disabled homolog 1 (Drosophila) | DAB1 | -8.91 | <0.05 |
| mal, T-cell differentiation protein 2 | MAL2 | -21.75 | <0.05 |
| nebulette | NEBL | -26.72 | <0.05 |
| death associated protein-like 1 | DAPL1 | -28.69 | <0.05 |
| hydroxysteroid (17-beta) dehydrogenase 1 | HSD17B1 | -35.75 | <0.05 |
Primer sequences (5′-3′)
| integral membrane protein 2A | ITM2A | TCTCGTAGGCCTTTCCTTCA |
| disabled homolog 1 (Drosophila) | DAB1 | TACGTTTGTGGGAAGGAAGG |
| mal, T-cell differentiation protein 2 | MAL2 | AGGATGGGTCATGTTCGTGT |
| nebulette | NEBL | CAAACCCTTCAAGGCTACCA |
| death associated protein-like 1 | DAPL1 | CCTGCTCTGGAGAAGGTCAC |
| hydroxysteroid (17-beta) dehydrogenase 1 | HSD17B1 | GTGTCAGAGGCTTGCTAGGG |
The Affymetrix® Porcine Gene 1.1 ST Array Strip for the microarray gene expression was employed for the analysis of porcine granulosa cells. The array method allowed us to study the gene expression of 27,558 transcripts at 0, 48, 96 and 144h of
FIGURE 1
Heatmaps presenting differentially expressed genes involved in “developmental process”, “cellular developmental process”, “regulation of cell differentiation”, “epithelium migration”, “epithelial cell proliferation”, “epithelial cell migration”, “epithelial cell differentiation”, “epithelial cell development”, “endodermal cell differentiation”, “endoderm formation”, “endoderm development” and “epithelium development” based on GO BP terms. Each row on the Y axis represents a single transcript. The red color indicates downregulated genes while the green are upregulated
z-scores analysis reveals whether molecular function is more likely to be decreased (negative value) or increased (positive value). The z-scores were presented as segments of inner circles in the
FIGURE 2
The circular scatter plots of differentially expressed genes involved in “developmental process”, “cellular developmental process”, “regulation of cell differentiation”, “epithelium migration”, “epithelial cell proliferation”, “epithelial cell migration”, “epithelial cell differentiation”, “epithelial cell development”, “endodermal cell differentiation”, “endoderm formation”, “endoderm development” and “epithelium development” GO BP terms. Each dot represents a single gene. The z-scores were presented as segments of inner circles
The interaction between selected ontological groups was examined and and are presented in as dendrogram (
FIGURE 3
The dendrogram of differentially expressed genes involved in “developmental process”, “cellular developmental process”, “regulation of cell differentiation”, “epithelium migration”, “epithelial cell proliferation”, “epithelial cell migration”, “epithelial cell differentiation”, “epithelial cell development”, “endodermal cell differentiation”, “endoderm formation”, “endoderm development” and “epithelium development” GO BP terms. The DEGs were clustered based on their logFC values
In the gene ontology database, single genes may belong to many ontological terms. For this reason, we used plots with visualization of logFC values and relationship between genes and selected GO BP terms (
FIGURE 4
Analysis of enriched gene ontological groups involved in regulation of granulosa cells differentiation towards endodermal and epithelial tissues. The network plot presenting the linkages of genes and GO BP terms
FIGURE 5
Heatmap presenting the relationship between genes and selected GO BP terms. The yellow color of tiles indicates the absence of logFC values
Finally, we used ReactomeFIViz app for investigation of functional interactions between proteins encoded by DEGs belonging to selected GO BP terms. Among the most significantly enriched functional interaction networks was FI networks for “positive regulation of cell proliferation” (
FIGURE 6
Reactome FI network for “positive regulation of cell proliferation”. “--->” indicates activating/catalyzing, “-|” for inhibition, “-” FIs extracted from complexes or inputs and “---” predicted FIs
Genes involved in the following processes: “developmental process”, “cellular developmental process”, “regulation of cell differentiation”, “epithelium migration”, “epithelial cell proliferation”, “epithelial cell migration”, “epithelial cell differentiation”, “epithelial cell development”, “endodermal cell differentiation”, “endoderm formation”, “endoderm development” and “epithelium development” were validated (
FIGURE 7
Microarray validation using RT-qPCR
Several recent studies have suggested that every tissue and organ contain a population of cells with stem-like properties, including the ovary [13,14,15]. Stem cells were found both in mouse and human ovaries, and they were observed to be involved in the processes of oogenesis and folliculogenesis. Specifically, granulosa cells (GCs) show programmed stem cell properties during
Further understanding of the molecular basis underlying these processes and of the cells in the reproductive system may reveal the functioning of determined clinical diseases, potentially leading to therapies and treatments of diverse conditions, such as infertility. Microarray analyses identified a group of genes with altered levels of expression. Some of these affected genes are associated with cell development and differentiation towards endodermal and epithelial tissues.
Epithelial tissue shows polarization. In many cases, neoplastic transformation is accompanied by the loss of the polarized phenotype typical of epithelial cells. Apical transport of protein takes place in epithelial tissue in two ways: direct and indirect pathways. Proteins transported indirectly are first directed to the basolateral surface. After proteins undergo endocytosis and are directed further to the apical surface by the transcryptotic pathway [20]. One of the proteins that play an important role in indirect protein transport is the MAL protein family, which has been detected in many normal epithelial cells isolating from the respiratory system, gastrointestinal tract, genitourinary tract and endocrine glands. Specific changes in MAL (T-cell differentiation protein) and MAL2 (T-cell differentiation protein 2) expression have been observed in certain types of cancer[21]. Lak et al. suggest that overexpression of MAL2 may promote the proliferation of breast cancer cells, while its knockout may reduce the proliferation of breast cancer cancer cells [22]. A study by Zhou et al. suggest that tumor tissue cells and breast cancer cell lines showed decreased expression of ITM2A (integral membrane of 2A protein). On the other hand, overexpression of this gene significantly inhibited the proliferation of breast cancer cells, which qualifies ITM2A as a prognostic marker [23]. Moreover, the ITM2A gene, encoding a porcine protein that is highly homologous to the integrated 2A (ITM2A) membrane protein of humans and mice, was herby downregulated. The expression of this gene is observed in fat, spleen, lungs, muscles, liver, small intestine, large intestine and kidneys [24]. ITM2A was also observed to have a therapeutic potential for epithelial ovarian cancer, as it acts as a chemosensitizer and induces cell cycle arrest [25].
The experimental gene overexpression also had an inhibitory effect on the proliferation of breast cancer, DAB1 (DAB protein adaptor 1) [26].This gene encodes for an adaptive protein necessary for intracellular Reelin signal transmission, which, in turn, controls the migration and differentiation of postmitotic neurons in the brain development process [27]. Moreover, this gene plays important roles in cell morphogenesis, differentiation and development, specifically in neuronal differentiation of granulosa cells [28].
Next downregulated gene is NEBL (nebulette). This gene encodes a nebulin-like protein that binds to actin and is highly expressed in the myocardium, playing an important role in Z-disk assembly [29]. It is abundant in the heart muscle, especially in the myocardium, where it assembles cardiac myofibril, combining sarcomeric actin with desmin fibers in sarcomeres [30,31].
Another gene showing downregulated expression in the presented studies is DAPL1 (death associated protein-like 1). This gene is involved in the early stages of epithelial differentiation, but also in the processes of apoptosis. Increased levels of expression of DAPL1 were observed in studies on uterine inflammation in dairy cows, analyzing levels of its transcripts in the endometrium [32]. It may show a different level of expression depending on the tissue [33]. Moreover, Chen et al. proved that DAPL1 is an important factor regulating steroidogenesis [34]. Zhang et al. noted that DAPL1 is less expressed in breast cancer cells than in other healthy tissues. Low expression of this gene was correlated with poor prognosis of survival in patients with breast cancer [35].
Finally, HSD17B1 was the most downregulated gene. Its product enzyme catalyzes the conversion of estrone to estradiol, and genetic variations of this gene are associated with the risk of breast and endometrial cancer, as well as modifying the susceptibility to endometriosis [36,37]. Its expression is observed in ovaries, placenta, testis, endometrium, malignant and normal breast epithelium, and prostatic cancer cells [38,39].
The changes in expression during long-term primary
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FIGURE 7
The 6 most downregulated genes involved in regulation of granulosa cells differentiation towards endodermal and epithelial tissues were validated using RT-qPCR, 168h/0h
| integral membrane protein 2A | ITM2A | -8.85 | <0.05 |
| disabled homolog 1 (Drosophila) | DAB1 | -8.91 | <0.05 |
| mal, T-cell differentiation protein 2 | MAL2 | -21.75 | <0.05 |
| nebulette | NEBL | -26.72 | <0.05 |
| death associated protein-like 1 | DAPL1 | -28.69 | <0.05 |
| hydroxysteroid (17-beta) dehydrogenase 1 | HSD17B1 | -35.75 | <0.05 |
Primer sequences (5′-3′)
| integral membrane protein 2A | ITM2A | TCTCGTAGGCCTTTCCTTCA |
| disabled homolog 1 (Drosophila) | DAB1 | TACGTTTGTGGGAAGGAAGG |
| mal, T-cell differentiation protein 2 | MAL2 | AGGATGGGTCATGTTCGTGT |
| nebulette | NEBL | CAAACCCTTCAAGGCTACCA |
| death associated protein-like 1 | DAPL1 | CCTGCTCTGGAGAAGGTCAC |
| hydroxysteroid (17-beta) dehydrogenase 1 | HSD17B1 | GTGTCAGAGGCTTGCTAGGG |
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