The oviduct (uterine tube or Fallopian tube) of the domestic mammals plays a crucial role in providing an optimal microenvironment for final gamete maturation and transport, fertilization, and early embryo development [1]. Moreover, these main functions of the oviduct are highly based on its contractibility, the capacity of secreting oviductal fluid into the lumen and other oviductal components include hormones, growth factors and their receptors [2]. The characteristic feature of oviduct epithelial cells (OECs) are cilia, which facilitate the transport of the oocyte and/or the embryo. The rest of the cells in the OECs are secretory cells, that produce fluid secreted into the fallopian tube. The histological architecture of oviducts undergo substantial modification as response to reproductive cycle during lifespan of females.
Establishment and characterization of
Recent experiments indicated that the gene expression profile changes within the OECs was also accompanied by significant changes in cellular proliferation capability
The gene expression profile in OECs primary cultured for a long-time using microarray assays is demonstrated in this study, as part of a project aimed at the molecular characterization of this cell population. Affymetrix microarray assays identified the regulatory peptides and enzymes involved in nucleotide, ribonucleotide and ribonucleoside binding pathways. In this study we demonstrated the transcripts expression variability of genes belonging to “adenyl nucleotide binding”, “adenyl ribonucleotide binding”, “ribonucleotide binding”, “ribonucleoside binding” gene ontology biological process terms (GO BP) during OECs long-term primary culture
Nine month old crossbred gilts (n=45) that displayed two regular estrous cycles were collected from a commercial herd. All the animals were checked daily for estrus behavior and were slaughtered after reaching the anestrus phase of the estrus cycle. The uteri were then transported to the laboratory within 30 min at 38 °C.
Oviducts were washed twice in Dulbecco’s phosphate buffered saline (PBS) (137 mM NaCl, 27 mM KCl, 10 mM Na2 HPO4, 2 mM KH2PO4, pH 7.4). Epithelial cells were surgically removed using sterile surgical blades. Then, the epithelium was incubated with collagenase I (Sigma Aldrich, Madison, USA), 1mg/mL in Dulbecco’s modified Eagle’s medium (DMEM; Sigma Aldrich, Madison, USA) for 1h at 37°C. The cell suspension obtained from this digestion was filtered through 40 μm pore size strainer to remove blood and single cells. The residue was collected by rinsing the strainer with DMEM. The cells were centrifuged (200 g, 10 min), washed in PBS and centrifuged again. Then, the cells were incubated with 0.5% Trypsin/EDTA (Sigma Aldrich, Madison, USA) at 37°C for 10 min. The reaction was stopped with fetal calf serum (FCS; Sigma Aldrich, Madison, USA). After incubation, cells where filtered and centrifuged again. The final cell pellet was suspended in DMEM supplemented with 10% FCS, 100 U/mL penicillin, 100 μg/mL streptomycin and 1μg/mL amphotericin B. The cells were cultured at 37°C in a humidified atmosphere of 5% CO2. Once the OECs cultures attained 70–80% confluency, they were washed with PBS and passaged. The passage procedure involves cell digestion with 0.025% Trypsin/EDTA, enzyme neutralization, centrifugation of samples, and resuspension at a seeding. The culture medium was changed every three days.
Oviductal epithelial cell were pooled (10 replicates) and harvested at 24h, 7 days, 15 days and 30 days after the beginning of
Total RNA (100 ng) from each pooled sample was subjected to two rounds of sense cDNA amplification (Ambion® WT Expression Kit, provided by Ambion, Austin, TX, USA). The synthesis of cRNA was performed by in vitro transcription (16 h, 40 °C). Then, cRNA was purified and retranscribed into cDNA. Subsequently, cDNA samples were used for biotin labeling and fragmentation using an Affymetrix GeneChip® WT Terminal Labeling and Hybridization kit (Affymetrix). Next, the biotin-labeled samples were loaded onto and hybridized to the Affymetrix® Porcine Gene 1.1 ST Array Strip (48°C/20 h). Hybridization was conducted at 48 °C for 20 h, employing an AccuBlock™ Digital Dry Bath (Labnet International, Inc., Edison, NJ, USA) hybridization oven. Microarrays were washed and stained, according to technical protocol, using an Affymetrix GeneAtlas™ Fluidics Station (Affymetrix, Santa Clara, CA, USA). The strips were scanned using an Affymetrix GeneAtlas™ Imaging Station (Affymetrix, Santa Clara, CA, USA). The scans of the microarrays were saved on hard drives as *.CEL files for downstream data analysis.
All of the presented analyses and graphs were performed using Bioconductor and R programming languages. Each *.CEL file was merged with a description file. In order to correct background, normalize, and summarize results, we used the Robust Multi-array Averaging (RMA) algorithm. To determine the statistical significance of the analyzed genes, moderated t-statistics from the empirical Bayes method were performed. The obtained p-value was corrected for multiple comparisons using Benjamini and Hochberg’s false discovery rate. The selection of significantly altered genes was based on a p-value beneath 0.05 and expression higher than two fold.
Differentially expressed genes were subjected selection by examination of genes involved in cell migration regulation. The differentially expressed gene list (separated for up- and down-regulated genes) was uploaded to DAVID software (Database for Annotation, Visualization and Integrated Discovery) [9], where genes belonging to the terms of all three Gene Ontology (GO) domains were extracted. Expression data of these genes were also subjected to a hierarchical clusterization procedure, and their expression values were presented as a heat map.
Subsequently the relation between the genes belonging to chosen GO terms were analyzed with GOplot package [10]. The GoPlot package had calculated the z-score: the number of up- regulated genes minus the number of down- regulated genes divided by the square root of the count. This information allowed estimating the change course of each gene-ontology term.
Interactions between differentially expressed genes/proteins belonging to the studied gene ontology group were investigated by STRING10 software (Search Tool for the Retrieval of Interacting Genes) [11]. The list of gene names was used as a query for an interaction prediction. The search criteria were based on co-occurrences of genes/proteins in scientific texts (text mining), co-expression, and experimentally observed interactions. The results of such analyses generated a gene/protein interaction network where the intensity of the edges reflected the strength of the interaction score.
The research has been complied with all the relevant national regulations, institutional policies and in accordance the tenets of the Helsinki Declaration, and has been approved by the authors’ institutional review board or equivalent committee. Poznan University of Medical Sciences Bioethics Committee approval no. 32/2012 from June 1, 2012.
Whole transcriptome profiling by Affymetrix microarray allowed the analyzation of gene expression changes between 7, 15 and 30 days of porcine oviductal epithelial cells culture. Through use of Affymetrix® Porcine Gene 1.1 ST Array Strip, we examined expression of 12257 transcripts. Genes with fold change higher than abs (2) and wit corrected p-value lower than 0.05 were considered as differentially expressed. This set of genes consisted of 2533 different transcripts. The first detailed analysis was based on GO BP identification of differentially expressed genes belonging to the significantly enrichment GO BP terms.
DAVID (Database for Annotation, Visualization and Integrated Discovery) software was used for extraction of gene ontology biological process term (GO BP) that contains differently expressed transcripts. Up- and down-regulated gene sets were subjected to DAVID searching separately and only the gene sets which had an adj. p-value lower than 0.05 were selected. The analysis of the DAVID software showed that there were 657 differentially expressed genes belonging to the Gene ontology terms. In this paper, we focused on 222 genes that belong to “adenyl nucleotide binding”, “adenyl ribonucleotide binding”, “ribonucleotide binding”, “ribonucleoside binding” GO BP terms. These sets of genes were subjected to the hierarchical clusterization procedure and presented as heatmaps (
Gene symbols, fold change in expression ratio, Entrez gene IDs, corrected p values and mean value of fold change ratio of the 20 chosen differentially expressed, studied genes
GENE SYMBOL | RATIO D7/D1 | RATIO D30/D1 | RATIO D15/D1 | ADJUSTED P.VALUE D7/D1 | ADJUSTED P.VALUE D15/D1 | ADJUSTED P.VALUE D30/D1 | ENTREZ GENE ID | MEAN RATIO |
---|---|---|---|---|---|---|---|---|
OASL | -19.013577 | -19.59127971 | -20.33618335 | 2.69E-05 | 1.34E-05 | 7.93E-06 | 595119 | -19.64701335 |
PIM1 | -2.278169547 | -7.702016846 | -14.75410523 | 0.000841907 | 7.24E-06 | 1.14E-06 | 100157844 | -8.244763875 |
RAB27A | -2.438418171 | -6.421074057 | -12.17306946 | 0.000240688 | 4.70E-06 | 7.36E-07 | 606749 | -7.010853897 |
ERBB3 | -3.700854877 | -8.072357208 | -8.474685238 | 4.67E-05 | 3.53E-06 | 1.48E-06 | --- | -6.749299107 |
DDX60 | -9.539122077 | -5.148779 | -4.690032007 | 7.61E-05 | 0.000244171 | 0.000232065 | --- | -6.459311028 |
NAV3 | -2.570715662 | -3.817701681 | -12.08344185 | 0.005032343 | 0.000725275 | 2.01E-05 | --- | -6.157286398 |
MX2 | -8.476906188 | -5.025767174 | -2.864164098 | 3.11E-05 | 6.87E-05 | 0.000433456 | 396893 | -5.455612486 |
MCM4 | -1.824811573 | -2.553654794 | -11.20276401 | 0.001672766 | 0.000140647 | 8.81E-07 | 100156398 | -5.193743459 |
DHX58 | -6.093081701 | -5.06259312 | -3.519635478 | 2.24E-05 | 1.83E-05 | 4.23E-05 | 100524520 | -4.891770099 |
OAS1 | -4.734227264 | -4.803325858 | -4.579644931 | 0.000637714 | 0.000454579 | 0.00038381 | --- | -4.705732684 |
CFTR | 5.930096417 | 5.971243553 | 3.580726141 | 4.73E-05 | 2.79E-05 | 0.000103206 | 403154 | 5.160688703 |
BVES | 5.084835235 | 6.889451287 | 4.958469165 | 0.000164789 | 4.63E-05 | 7.99E-05 | 100153106 | 5.644251896 |
NUAK1 | 5.90004438 | 7.687798942 | 4.205418788 | 2.17E-05 | 5.48E-06 | 1.88E-05 | 100523669 | 5.93108737 |
PANK1 | 7.855561899 | 3.491673705 | 7.158649931 | 7.45E-06 | 3.27E-05 | 2.08E-06 | 100154650 | 6.168628512 |
ACAA2 | 4.821347296 | 6.223974104 | 7.791004625 | 1.04E-05 | 3.05E-06 | 8.03E-07 | 100312959 | 6.278775342 |
FGFR1 | 4.599714105 | 5.650775055 | 8.942976069 | 1.33E-05 | 3.63E-06 | 6.88E-07 | 100153248 | 6.397821743 |
P2RX7 | 6.165142343 | 8.522042354 | 5.795397835 | 2.69E-05 | 6.72E-06 | 1.03E-05 | 497623 | 6.827527511 |
KIF23 | 6.496859984 | 7.105965066 | 7.104751913 | 0.000646977 | 0.000381978 | 0.000271214 | 100522116 | 6.902525654 |
ABCA1 | 6.313396076 | 5.556746901 | 10.33557918 | 3.95E-05 | 3.12E-05 | 4.36E-06 | 100152112 | 7.401907384 |
ACTA2 | 5.225241405 | 12.54084054 | 30.24621828 | 3.15E-05 | 3.09E-06 | 4.37E-07 | 733615 | 16.00410008 |
The enrichment of each GO BP term was calculated as a z-score and shown on the circle diagram (
Chosen GO BP terms contain 222 differentially expressed genes. Therefore, we calculated the mean value of mean of fold change ratio of each gene between 7, 15 and 30 days of culture. Based on that criteria we chose the 10 most down-regulated and the 10 most up-regulated genes to further analysis.
In Gene Ontology database genes that formed one particular GO group can also belong to other different GO term categories. By this reasoning, we explored the gene intersections between selected GO BP terms. The relation between those GO BP terms was presented as circle plot (
STRING-generated an interaction network among differentially expressed genes belonging to each of the selected GO BP terms. Using such a prediction method provided a molecular interaction network formed between protein products of studied genes (
The morphological modifications of oviducts in response to the female reproductive cycle are well established [12]. However, detailed characterization at the molecular level remains a unresolved. Establishment and depiction of primary cell cultures
From the whole transcript profile after the microarray assay, during long-term
The PIM family of serine/threonine kinase proteins consists of three, highly homologous, isoforms PIM1, PIM2 and PIM3. The PIM genes’ expression is induced by a variety of cytokines, growth factors and mitogens [21]. The Pim1, as pro-survival kinase, has been implicated in tumorigenesis at different levels, especially in the control of cancer cells proliferation, migration and apoptosis [22]. These proteins have been labeled as “weak oncogenes” given that their overexpression induces hyperproliferation but no tumors in many cases [23]. Subsequent studies by Jiménez-García et al. [24] have described generation of two conditional PIM1 and PIM2 transgenic mice that overexpress PIM1 or PIM2 in mammary gland, uterus and ovary to characterize the proto-oncogenic role of PIM1/PIM2 in female hormone-dependent tissues. PIM1/2 overexpression induced hyperproliferation and tumors in the female reproductive system and evoked a high inflammatory response and stem markers [24]. Other research highlighted the role of Pim1 in ovarian cancer (OC) development [25]. Currently, it appears that Pim1 is overexpressed in OC and is correlated with the poor overall survival of patients. Moreover, Pim1 may significantly enhance glycolysis in OC cells. In conclusion, these results suggest that silencing or overexpressing Pim1 can suppress or promote OC cell proliferation [25].
In comparison, the presence of numerous genes, within the analyzed ontological groups, with a different mRNA expression pattern during the culture was demonstrated. We observed a growing transcript levels for subsequent measurement points during long-term cultivation. Definitely the highest upward trend was shown by
A member of the ATP-binding cassette (ABC) family,
The current results characterize a large scale the transcriptomic profile of this cell population during long-term in vitro culture. The results presented in this paper indicate potential markers whose decreased expression during the cultivation may affect the reduction of activity, cell viability.