The trabecula culture system: a novel technique to study contractile parameters over a multiday time period

1998 ◽  
Vol 274 (5) ◽  
pp. H1481-H1488 ◽  
Author(s):  
P. M. L. Janssen ◽  
S. E. Lehnart ◽  
J. Prestle ◽  
J. C. Lynker ◽  
P. Salfeld ◽  
...  
Keyword(s):  
Gene Expression ◽  
Protein Expression ◽  
Contractile Function ◽  
Expression Patterns ◽  
Leucine Incorporation ◽  
System A ◽  
Time Period ◽  
Incorporation Assay ◽  
Force Time ◽  
Ventricular Trabeculae

In the intact heart, various triggers induce alterations in gene expression that impact on contractile function. Because changes in gene expression reflect altered protein expression patterns after 12–48 h, we developed a system in which intact twitching cardiac trabeculae can be studied for multiday periods. Right ventricular trabeculae from pentobarbital sodium-anesthetized rabbits were mounted in a sterile, closed muscle chamber. Over the first 48 h, developed force (Fdev) did not significantly change: 102.3 and 98.9% of the initial Fdev was observed after 24 and 48 h, respectively ( n = 8). Also, neither diastolic force, time from peak to 50% relaxation (RT50), nor protein synthesis measured by a [3H]leucine incorporation assay changed significantly over time. Contractile response after >48 h to an increase in extracellular calcium concentration (1.8 to 2.5 mM; Fdevincreased 43.5%, n = 2) or to 1 μM isoproterenol (Fdevincreased 138.6% and RT50decreased 34.9%, n = 2) was similar to those observed in freshly dissected preparations. In conclusion, this system can investigate contractile function of multicellular preparations under well-defined physiological conditions after events that alter gene and consequent protein expression.

scholarly journals Microarray Analyses of Gene Expression during Chondrocyte Differentiation Identifies Novel Regulators of Hypertrophy

2005 ◽  
Vol 16 (11) ◽  
pp. 5316-5333 ◽  
Author(s):  
Claudine G. James ◽  
C. Thomas G. Appleton ◽  
Veronica Ulici ◽  
T. Michael Underhill ◽  
Frank Beier
Keyword(s):  
Gene Expression ◽  
Bone Development ◽  
Skeletal Development ◽  
Expression Patterns ◽  
Chondrocyte Differentiation ◽  
Endochondral Bone ◽  
Temporal Gene Expression ◽  
Affymetrix Microarrays ◽  
Time Period ◽  
And Cluster Analysis

Ordered chondrocyte differentiation and maturation is required for normal skeletal development, but the intracellular pathways regulating this process remain largely unclear. We used Affymetrix microarrays to examine temporal gene expression patterns during chondrogenic differentiation in a mouse micromass culture system. Robust normalization of the data identified 3300 differentially expressed probe sets, which corresponds to 1772, 481, and 249 probe sets exhibiting minimum 2-, 5-, and 10-fold changes over the time period, respectively. GeneOntology annotations for molecular function show changes in the expression of molecules involved in transcriptional regulation and signal transduction among others. The expression of identified markers was confirmed by RT-PCR, and cluster analysis revealed groups of coexpressed transcripts. One gene that was up-regulated at later stages of chondrocyte differentiation was Rgs2. Overexpression of Rgs2 in the chondrogenic cell line ATDC5 resulted in accelerated hypertrophic differentiation, thus providing functional validation of microarray data. Collectively, these analyses provide novel information on the temporal expression of molecules regulating endochondral bone development.

Molecular profiling of small cell bladder cancer (SCBC) to reveal gene expression determinants of an aggressive phenotype.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. 4529-4529 ◽  
Author(s):  
Vadim S. Koshkin ◽  
Jordan Reynolds ◽  
Paul Elson ◽  
Cristina Magi-Galluzzi ◽  
Jesse McKenney ◽  
...  
Keyword(s):  
Gene Expression ◽  
Protein Expression ◽  
Expression Patterns ◽  
Cleveland Clinic ◽  
Molecular Profiling ◽  
Small Cell ◽  
Gene Expression Patterns ◽  
Bladder Tissue ◽  
Normal Bladder ◽  
L1 Protein

4529 Background: SCBC is rare and its underlying biology poorly understood. Molecular profiling can shed light on the biology and identify treatment targets and biomarkers. Methods: A retrospective review of 63 patients (pts) with biopsy-confirmed SCBC at Cleveland Clinic (1994-2015) was performed. Percentage of small cell component (SC%) was defined by independent pathology review. DLL3 and PD-L1 protein expression were measured by IHC in 53 pts. Gene expression analysis was done in 38 primary SCBC tumor samples, 1 metastatic sample, and 5 normal bladder tissue samples (44 total) from the same cohort using HTG EdgeSeq OBP Assay with probes for 2568 genes. Analysis was performed via the RNAseq workflow (Partek Genomics Suite). Results: Among 63 identified pts, median age was 71 (39-90), 83% were men, median SC% was 100% (range 5-100%), median follow-up was 16.6 months and estimated median overall survival (OS) was 22.8 months. Unsupervised hierarchical clustering of gene expression patterns from 44 samples produced 4 distinct clusters. Pts with tumors in cluster 1 (that also included normal samples) did not have metastasis at diagnosis or distant recurrence, both of which were over-represented in the other 3 clusters. Kaplan-Meier analysis revealed a trend towards longer OS in cluster 1 patients (log rank p = 0.065). Higher gene expression of PRC1, NCAM1 (CD56) and DLL3 correlated with higher SC%, as did lower gene expression of ERBB2, PD-L1 and HPGD (p < 0.01). PD-L1 protein expression (≥1% cells) was noted in 30% of pts but did not correlate with outcome, SC%, DLL3 protein expression, or PD-L1 gene expression. DLL3 protein expression (≥1% cells) was noted in 68% of pts and DLL3 > 10% correlated with decreased OS (p = .03). Higher DLL3 protein expression correlated with DLL3 gene expression (Spearman r = 0.70, p < .01) and with SC% (r = .33, p = .01). Conclusions: This is the first study to reveal distinct gene expression patterns that define aggressive behavior, metastatic potential and outcomes in SCBC. The prognostic value of differential gene expression networks and the presence of underlying genomic and epigenetic alterations is the subject of ongoing prospective validation in a larger cohort.

scholarly journals Natural Genetic Variation Modifies Gene Expression Dynamics at the Protein Level During Pheromone Response in Saccharomyces cerevisiae

2016 ◽  
Author(s):  
Daniel A. Pollard ◽  
Ciara K. Asamoto ◽  
Homa Rahnamoun ◽  
Austin S. Abendroth ◽  
Suzanne R. Lee ◽  
...  
Keyword(s):  
Gene Expression ◽  
Protein Synthesis ◽  
Genetic Variation ◽  
Steady State ◽  
Protein Expression ◽  
Expression Patterns ◽  
Synthesis Rate ◽  
Protein Synthesis Rate ◽  
Mrna Levels ◽  
Expression Divergence

ABSTRACTHeritable variation in gene expression patterns plays a fundamental role in trait variation and evolution, making understanding the mechanisms by which genetic variation acts on gene expression patterns a major goal for biology. Both theoretical and empirical work have largely focused on variation in steady-state mRNA levels and mRNA synthesis rates, particularly of protein-coding genes. Yet in order for this variation to affect higher order traits it must lead to differences at the protein level. Variation in protein-specific processes including protein synthesis rates and protein decay rates could amplify, mask, or even reverse effects transmitted from the transcript level, but the extent to which this happens is unclear. Moreover, mechanisms that underlie protein expression variation under dynamic conditions have not been examined. To address this challenge, we analyzed how mRNA and protein expression dynamics covary between two strains ofSaccharomyces cerevisiaeduring mating pheromone response. Although divergentsteady-statemRNA expression levels explained divergentsteady-stateprotein levels for four out of five genes in our study, the same was true for only one out of five genes for expressiondynamics. By integrating decay rate and allele-specific protein expression analyses, we resolved that expression divergence for Fig1p was caused by genetic variation acting intranson protein synthesis rate, expression divergence for Ina1p was caused bycis-by-transepistatic effects on transcript level and protein synthesis rate, and expression divergence for Fus3p and Tos6p were caused by divergence in protein synthesis rates. Our study demonstrates that steady-state analysis of gene expression is insufficient to understand the impact of genetic variation on gene expression variation. An integrated and dynamic approach to gene expression analysis - comparing mRNA levels, protein levels, protein decay rates, and allele-specific protein expression - allows for a detailed analysis of the genetic mechanisms underlying protein expression divergences.

scholarly journals Single Cell Multi-Omic Profiling of Multiple Myeloma with t(4;14) Finds an Immune Microenvironment Gene Signature That Correlates with Clinical Outcomes

Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 2653-2653
Author(s):  
Sanjay De Mel ◽  
Jonathan Adam Scolnick ◽  
Chern Han Yong ◽  
Xiaojing Huo ◽  
Stacy Xu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
Protein Expression ◽  
Single Cell ◽  
Research Funding ◽  
Plasma Cells ◽  
Expression Patterns ◽  
Gene Signature ◽  
Response To Therapy ◽  
Diagnostic Samples

Abstract Background Multiple Myeloma (MM) is an incurable plasma cell (PC) malignancy and high risk MM remains an unmet clinical need. Translocation 4;14 occurs in 15% of MM and is associated with an adverse prognosis. A deeper understanding of the biology and immune micro-environment of t(4;14) MM is necessary for the development of effective targeted therapies. Single Cell multi-omics provides a new tool for phenotypic characterization of MM. Here we used Proteona's ESCAPE™ single cell multi-omics platform to study a cohort of patients with t(4;14) MM. Methods Diagnostic bone marrow (BM) samples from 13 patients with t(4;14) MM (one of whom had samples at diagnosis and relapse) were analysed using the ESCAPE™ platform from Proteona which simultaneously measures gene and cell surface protein expression of 65 proteins in single cells. Cryopreserved BM samples were stained with antibodies and subsequently sorted on CD138 expression. The CD138 positive and negative fractions were recombined at a 1:1 ratio for analysis using the 10x Genomics 3' RNAseq kit. Resulting data were analyzed with Proteona's MapSuite™ single cell analytics platform. In particular, Mapcell was used to annotate the cells and MapBatch was used for batch normalization in order to preserve rare cell populations. Results Patients had a median age of 63 years and received novel agent-based induction. Median progression free and overall survival (PFS and OS) were 22 and 34 months respectively. We first analyzed serial BM samples from an individual patient that were taken at diagnosis and relapse following bortezomib based treatment. The PCs in this patient showed variations in gene expression between diagnosis and relapse (Fig 1A), including the reduction of HIST1H2BG expression, which has previously been correlated with resistance to bortezomib. Subsequent analysis of the immune cells identified a shift in the ratio of T cells to CD14 monocytes from 5.7 at diagnosis to 0.6 at relapse suggesting a major change in the BM immune micro-environment in response to therapy. Next, we analyzed the malignant PCs of the diagnostic samples. As expected, MMSET (NSD2) was overexpressed in all PCs compared to normal PCs, while FGFR3 expression could be categorized into no expression of FGFR3, low expression (&lt;10% of cells expressing FGFR3) or high expression (&gt;80% of cells expressing FGFR3) (Fig 1B). No gene or protein expression patterns within the PCs were identified that correlated with PFS or OS in this cohort. Finally, we analyzed the immune micro-environment in the diagnostic samples (Fig 1C). While there was no overall discernable pattern of cell types present, one cluster of cells, annotated as 'unknown' cell type, suggested a small population of cells that had not been previously annotated in published single cell RNA-seq data. The cells were CD45+ and CD138 - both at the protein and RNA level, suggesting they are not plasma cells. We tested if the number of the 'unknown' cells in each sample correlated with PFS, but there was no significant correlation. We then used these cells to derive a gene signature profile which was expressed in most of the cells in the 'unknown' cluster as well as a minor fraction of cells in other clusters including some PCs. The number of cells expressing the gene signature negatively correlated with PFS, with samples containing more cells expressing the signature having a lower PFS than samples with fewer signature positive cells (Fig 2). The correlation remained significant whether we included PCs in the analysis or not, but was not significant amongst only the PC population, suggesting that the cells responsible for the correlation are from the immune micro-environment. Conclusions We present the first application of single cell multi-omic immune profiling in high-risk MM and demonstrate that t(4;14) is a phenotypically heterogenous disease. While no consistent gene or protein expression patterns were identified within the malignant cell population, we did identify gene expression changes in a relapsed patient sample that may reflect key alterations in the PCs responsible for therapy resistance. In addition, we identified a gene signature expressed in a rare population of non-plasma cells that significantly correlated with PFS in this patient cohort. These data highlight the potential of single cell multi-omic analysis to identify immune micro-environmental signatures that correlate with response to therapy in t(4;14) MM. Figure 1 Figure 1. Disclosures Scolnick: Proteona Pte Ltd: Current holder of individual stocks in a privately-held company. Huo: Proteona Pte Ltd: Ended employment in the past 24 months. Xu: Proteona Pte Ltd: Current Employment. Chng: Amgen: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Novartis: Honoraria; Abbvie: Honoraria.

Disruption of the circadian clock within the cardiomyocyte influences myocardial contractile function, metabolism, and gene expression

2008 ◽  
Vol 294 (2) ◽  
pp. H1036-H1047 ◽  
Author(s):  
Molly S. Bray ◽  
Chad A. Shaw ◽  
Michael W. S. Moore ◽  
Rodrigo A. P. Garcia ◽  
Melissa M. Zanquetta ◽  
...  
Keyword(s):  
Gene Expression ◽  
Heart Rate ◽  
Circadian Clock ◽  
Contractile Function ◽  
Ex Vivo ◽  
Expression Patterns ◽  
Diurnal Variations ◽  
Acid Oxidation ◽  
Oxidation Rates ◽  
Myocardial Contractile

Virtually every mammalian cell, including cardiomyocytes, possesses an intrinsic circadian clock. The role of this transcriptionally based molecular mechanism in cardiovascular biology is poorly understood. We hypothesized that the circadian clock within the cardiomyocyte influences diurnal variations in myocardial biology. We, therefore, generated a cardiomyocyte-specific circadian clock mutant (CCM) mouse to test this hypothesis. At 12 wk of age, CCM mice exhibit normal myocardial contractile function in vivo, as assessed by echocardiography. Radiotelemetry studies reveal attenuation of heart rate diurnal variations and bradycardia in CCM mice (in the absence of conduction system abnormalities). Reduced heart rate persisted in CCM hearts perfused ex vivo in the working mode, highlighting the intrinsic nature of this phenotype. Wild-type, but not CCM, hearts exhibited a marked diurnal variation in responsiveness to an elevation in workload (80 mmHg plus 1 μM epinephrine) ex vivo, with a greater increase in cardiac power and efficiency during the dark (active) phase vs. the light (inactive) phase. Moreover, myocardial oxygen consumption and fatty acid oxidation rates were increased, whereas cardiac efficiency was decreased, in CCM hearts. These observations were associated with no alterations in mitochondrial content or structure and modest mitochondrial dysfunction in CCM hearts. Gene expression microarray analysis identified 548 and 176 genes in atria and ventricles, respectively, whose normal diurnal expression patterns were altered in CCM mice. These studies suggest that the cardiomyocyte circadian clock influences myocardial contractile function, metabolism, and gene expression.

Differential Expression of Genes Associated with Toll-Like Receptor-4 (TLR4) Signal Transduction Pathway in Lipopolysaccharide (LPS)-Activated Cord Blood (CB) vs. Adult Peripheral Blood (APB) Monocyte (Mo)-Derived Dendritic Cells (DC).

Blood ◽  
2004 ◽  
Vol 104 (11) ◽  
pp. 3444-3444
Author(s):  
Hong Jiang ◽  
Mary Brigid Bradley ◽  
Carmella van de Ven ◽  
Prakash Satwani ◽  
Laxmi Baxi ◽  
...  
Keyword(s):  
Gene Expression ◽  
Signal Transduction ◽  
Protein Expression ◽  
Expression Patterns ◽  
Signal Transduction Pathway ◽  
Gene Expression Patterns ◽  
Transduction Pathway ◽  
Rt Pcr ◽  
Cell Surface Molecule ◽  
Expression Of Genes

Abstract LPS activates immature DC via TLR4 and induces maturation of DC for initiating antigen presenting activity (Medzhitov; Nat Rev Immunol 2001). We have previously demonstrated decreased gene expression and protein production of IL-12, IL-15, IL-18 in activated CB MNC and decreased DC MLR (Lee/Cairo, Blood 1996; Qian/Cairo, Blood 1997; Wu/Cairo, Blood 100:3668 p51b 2002). Recently, we have identified differential gene expression patterns including differential immunoregulatory and chemokine genes in LPS-CB vs APB Mo by microarray (Jiang/Cairo, J. Immunol 2004). Since the myeloid lineage DC is derived from Mo, we sought to determine in LPS activated CB vs. APB DC, differential expressed genes that associate with TLR4-mediated signaling pathway. Briefly, Mo were purified from fresh CB or APB and cultured for 7 days with GM-CSF & IL-4 [immature DC (iDC)] and LPS [mature DC (mDC)]. Aliquots from iDC and mDC were analyzed for DC immunophenotype, morphology and DC allogeneic antigen activity. mRNA was isolated, reverse transcripted to cDNA, labeled & hybridized to oligonucleotides (Affymetrix, U133A). Data was analyzed by MAS 5.0 (Affymetrix) and GeneSpring 5.0 software (Silicon Genetics). Several genes were analyzed by RT-PCR (One-Step SuperScript, Invitrogen) and protein expression was analyzed by Western Blot (Bio-Rad). Inverted microscopy demonstrated DC mature morphology at day 8 and flow cytometry demonstrated decreased CD14 and increased CD83 expression in CB & APB mDC. We also demonstrated significant increase in the allogeneic stimulatory effects on CD4+ T cells in APB vs. CB mDC. The microarray analysis demonstrated a significant decreased gene expression of TLR4 [3 fold (F)] and CD14 (2.1 F) (p<0.05) in CB vs APB-DC. We further identified LPS significantly induced increased expression of TLR4 downstream signaling molecular genes such as MAPKKK, NF-kB and TANK in APB compared to CB mDC (3–8 F) (p<0.05). There were also significant amplifications of a variety of other gene categories in LPS activated APB vs CB mDC (p<0.05) including cell surface molecule CD80 (3.7F) and IL-2Ra (5.3 F), cytokine IL-23 (3.5F) & IL-12 (13 F), signal transduction STAT1 (3.4F) & IRF-7 (7.7 F), and immunoregulatory TNFSF10 (12F) & ISG20 (39F). Gene expression of NF-kB1, TRAF1 & IRF-7 by RT-PCR demonstrated an increased expression in LPS-APB vs CB mDC and were compatible with microarray. Moreover, Western analysis of IRF-7 demonstrated increased protein expression in LPS-APB vs CB mDC. In summary, we have identified decreased gene expression patterns in LPS-CB vs APB DC, especially those in the TLR4 signal transduction pathway (MAP3K, TRAF, TANK & NF-kB), and suggest these differentially expressed genes may enhance the activation of TLR4 pathway in LPS-APB vs CB DC, resulting in differential regulation of CB vs APB DC antigen presentation capacities. Furthermore, these decreased expressed genes in other molecular categories (e.g.IL-23, IFNg, IL6, CD80, STAT1, IRF-7, SOCS3) in LPS-CB vs APB DC may be partially responsible for differential innate and adaptive immune function of CB vs APB. Moreover, the differential regulated expression of genes may in part help to explain reduced incidence of severe aGVHD, delay in immune reconstitution and/or increased infectious mortality following HLA disparate UCBT.

scholarly journals Random Insertion of a TetR-Inducing Peptide Tag into Escherichia coli Proteins Allows Analysis of Protein Levels by Induction of Reporter Gene Expression

2006 ◽  
Vol 72 (8) ◽  
pp. 5637-5642 ◽  
Author(s):  
Maximilian Schlicht ◽  
Christian Berens ◽  
Janko Daam ◽  
Wolfgang Hillen
Keyword(s):  
Gene Expression ◽  
Escherichia Coli ◽  
Protein Expression ◽  
Reporter Gene ◽  
Expression Patterns ◽  
Reporter Gene Expression ◽  
Published Data ◽  
Insertion Element ◽  
Protein Levels ◽  
Fusion Protein Expression

ABSTRACT The insertion element InsTipα was constructed to generate protein expression data. It randomly fuses the TetR-inducing peptide Tip to the affected reading frame. Fusion protein expression is quantified by Tet-regulated reporter gene expression. The expression patterns of tagged Escherichia coli genes fully agree with published data from transcriptional fusions or microarrays, validating the Tip tag approach.

scholarly journals The AERO System: A 3D-Like Approach for Recording Gene Expression Patterns in the Whole Mouse Embryo

PLoS ONE ◽  
2013 ◽  
Vol 8 (10) ◽  
pp. e75754 ◽  
Author(s):  
Hirohito Shimizu ◽  
Atsushi Kubo ◽  
Kenta Uchibe ◽  
Megumi Hashimoto ◽  
Shigetoshi Yokoyama ◽  
...  
Keyword(s):  
Gene Expression ◽  
Mouse Embryo ◽  
Expression Patterns ◽  
Gene Expression Patterns ◽  
System A

Identification of integrin as potential molecular markers in human glioblastoma multiforme: Microarray analysis guided by contrast-enhanced MRI

2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 10007-10007
Author(s):  
Y. Yang ◽  
Y. Chia ◽  
D. Rubin ◽  
G. Harsh ◽  
S. Atlas ◽  
...  
Keyword(s):  
Gene Expression ◽  
Glioblastoma Multiforme ◽  
Protein Expression ◽  
Contrast Agent ◽  
Vascular Permeability ◽  
Immunohistochemical Staining ◽  
Expression Patterns ◽  
Expression Levels ◽  
Contrast Enhanced ◽  
Integrin Family

10007 Background: Glioblastoma multiforme (GBM) is a primary brain tumor with poor prognosis and low survival rate. It is characterized as a highly infiltrative and vascular tumor, with morphologic heterogeneity including necrosis regions. We have used contrast enhanced (CE)-MRI to identify regions that differ in vascular permeability as delineated by the small molecule contrast agent Magnevist. Non-necrotic areas with and without contrast enhancement were sampled in the OR. The expression profiles for integrin family genes were investigated and validated using IHC. Genes encoding for integrin subunits with high expression levels in these regions of the tumor were identified and are presented here. Methods: Patients diagnosed with GBM, without any prior procedures were scanned on a GE 1.5T MRI scanner using standard T1- and T2-weighted pulse sequences and Gd(DTPA) as contrast agent. Samples from regions with vascular permeability to the contrast agent (contrast-enhancing, CE) and vascular regions that are not permeable to the contrast agent (non-enhancing, NE) were collected for gene expression profiling using the Affymatrix oligonucleotide microarray system. Genomic data was normalized at probe-level, and analyzed using a modified t-test, Significance Analysis of Microarray (SAM). Significant expression levels were identified. Immunohistochemical staining was used to validate protein expression of selected genes of interest. Results: Tissue samples from the CE and NE regions of 13 patients reveal significantly distinct gene expression patterns. In specific, genes in the integrin family such as integrin αIIb, αV and β3 show high expression levels in the CE region. Immunohistochemical staining confirmed correlation of protein expression patterns with the observed genomic profile. Conclusions: Combination of CE-MRI using the clinical contrast agent and microarray analysis can reveal spatial genomic profiles correlated with imaging features associated with increased vascular permeability, vessel density, and areas of fluid accumulation. The identified genes from the integrin family can be potential molecular targets, and can be used for molecular imaging and therapeutic purposes. No significant financial relationships to disclose.

scholarly journals 124 THE MAJOR GENE EXPRESSION PATTERNS IN ENDOMETRIAL TISSUE OF PIGS DURING EARLY GESTATION

2005 ◽  
Vol 17 (2) ◽  
pp. 212
Author(s):  
B.-K. Kim ◽  
H.J. Chung ◽  
Y.G. Ko ◽  
Y.M. Kim ◽  
H.-H. Seong ◽  
...  
Keyword(s):  
Gene Expression ◽  
Estrogen Receptor ◽  
Protein Expression ◽  
Expression Patterns ◽  
Estrogen Receptor Α ◽  
Endometrial Tissue ◽  
Estrogen Receptor Β ◽  
Uterine Receptivity ◽  
Early Gestation ◽  
Tgf Β1

Although the expression of important genes in the embryo at pre-implantation stage, which encompasses the period from fertilization to implantation, have been reported for mice and cows, little information relevant to this subject is known in pigs. The objective of this study was to investigate the changes of importantly expressed genes and proteins in endometrial tissue of pigs from fertilization to implantation. Six genes, including estrogen receptor-α, estrogen receptor-β, LIF, LR (LIF receptor), TGFβ1, and TGFβ2, that may play important roles in regulating uterine receptivity and successful implantation and that show different expression patterns by the stages of pregnancy were selected. As a step toward understanding the role of gene and protein expression changes in endometrial tissue of pigs during the preimplantation stage (Day 2, Day 6, Day 8, Day 12, and Day 17, n = 3/group) and the post-implantation stage (Day 21 and Day 33, n = 3/group) and Day 0 (estrous), real-time PCR methods for quantitative analysis of genes and immunohistochemistry methods to localize protein expression were utilized. Data from quantitative real-time PCR were analyzed by ANOVA. The results of this experiment indicated that estrogen receptor-β mRNA level was sharply increased to Day 12 of pregnancy, while estrogen receptor-α mRNA did not change drastically during early pregnancy stage. In contrast, levels of LIF and LR mRNA were increased from Day 2 to Day 33. Although TGFβ1 mRNA reached peak on Day 17 and TGFβ2 mRNA showed the highest level on Day 17, TGFβ2 did not appear to change drastically. For the protein expression patterns, estrogen receptor-α and estrogen receptor-β proteins were expressed in both luminal epithelium and glandular epithelium, but they were only partially expressed in some tissues of stroma cells. LIF protein was expressed in all cell types, while TGF β1 protein was high expressed in glandular epithelium. Also, ERs, LIF, and TGF β1 mRNA and protein expression showed stage- and cell-specific expression patterns. We also investigated the gene expression of TGF β1 mRNA and TGF β2 mRNA in early conceptus (Day 12 and Day 17). TGF β1 mRNA expression was low in Day 12 embryos, and increased progressively to Day 17. This indicated that both the maternal uterus and the conceptus represent the same gene expression pattern. These results suggest that estrogen receptor-β could be an important factor in estrogen action in endometrial tissue during early gestation in pigs, and TGF βs function in both autocrine and paracrine interactions. Progressive increase in TGF β1 mRNA expression in conceptus and uterine tissues suggest important roles of TGF β1 in conceptus development and establishment of the uterine receptivity during the peri-implantation period.

Sign in / Sign up

Export Citation Format

Share Document