Mol. Hum. Reprod. Advance Access originally published online on November 29, 2007
Molecular Human Reproduction 2008 14(1):61-65; doi:10.1093/molehr/gam083
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Gene expression profile in labouring and non-labouring human placenta near term
1Department of Obstetrics and Gynaecology, University Hospital of North Norway and Institute of Clinical Medicine, University of Tromsø, PO Box 24, Tromsø N-9038, Norway 2Laboratory of Molecular Medical Research, Institute of Clinical Medicine, University of Tromsø, N-9037, Tromsø, Norway 3Department of Medical Genetics, University Hospital of North Norway, N-9037 Tromsø, Norway 5Present address: WesternGeco, Oslo Technology Center, Schlumberger House, 1372 Asker, Norway
4 Correspondence address. Tel: +47-776-26-000; Fax: +47-776-26-421; E-mail: vasilis.sitras{at}unn.no
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Abstract |
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The duration of pregnancy and initiation of labour are thought to be controlled by fetal, maternal and placental factors. The aim of this study was to investigate whether labour influences gene expression in placenta near term. Placental samples were obtained from 27 women after vaginal delivery (labouring) and 17 women after elective Caesarean section (non-labouring). All women were Caucasian and had uncomplicated pregnancies. For global gene expression analysis, 17 human oligo-arrays were used, representing 24 650 genes each. An empirical Bayes analysis was applied in order to find differentially expressed genes. About 8000 genes that were represented on the arrays met our quality criteria. Ninety two genes were down-regulated and 94 genes were up-regulated in labouring placentas compared to non-labouring placentas. However, none of these was differentially expressed at a significant level (>2.5-fold change and a P-value of <0.01). We conclude that gene expression in near term human placenta is not significantly altered by labour.
Key words: gene expression/parturition/placenta
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Introduction |
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TopAbstractIntroductionMaterials and methodsResultsDiscussionFundingAcknowledgementsReference |
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The duration of pregnancy and initiation of labour are thought to be controlled by an interplay of fetal, maternal and placental factors. Interactions of neurological (the fetal hypothalamic–pituitary–adrenal axis), hormonal (oxytocin, estrogen, progesterone and relaxin), mechanical (uterine-fibre stretching), electrical (gap junctions between myometrial cells) and inflammatory (cytokines) factors have been shown to have important roles in the initiation and maintenance of labour (Challis et al., 2000a). However, the mechanisms involved in maintenance of pregnancy, uterine activation and parturition are poorly understood. As a result, prediction and treatment of preterm labour remains difficult and prematurity continues to be an important cause of perinatal mortality and morbidity (Reedy, 2007).
Attempts have been made to elucidate the physiology of parturition using experimental animal models, ultrasound imaging and molecular biology techniques.
Microarray technology enables the investigation of the global gene expression profile in a given tissue at a given time. An increasing number of genomic studies are concentrating on the role of the placenta in feto-maternal diseases such as pre-eclampsia (Reimer et al., 2002; Hansson et al., 2006), intrauterine growth restriction (Roh, 1999) and miscarriage (Shimokawa et al., 2006). A few genomic studies have been performed on animal (Girotti and Zingg, 2003) and human (Chan et al., 2002; Rehman et al., 2003; Havelock et al., 2005) myometrium in order to find candidate genes involved in labour. During parturition, genes involved in inflammation and immune pathways as well as components of the extra-cellular matrix and hormone signalling have been found to be differentially expressed in a temporal–spatial manner.
The aim of our study was to investigate whether labour influences gene expression in placenta near term. We hypothesized that the genes involved in uterine contractions and uterine relaxation are up-regulated and down-regulated, respectively.
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Materials and methods |
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Study population
Placental samples were obtained from 50 women who delivered after 34 weeks of gestation: (i) vaginally (labouring) and (ii) by elective Caesarean section (non-labouring). All participants were Caucasian, healthy and had uncomplicated pregnancies. The study was approved by the Regional Committee for Medical Research Ethics and informed written consent was obtained from all the participants. All pregnant women recruited to the study had a physical examination and ultrasonography on admission to the hospital (
24 h before delivery) to exclude any significant maternal or fetal pathology. Outcome of pregnancy and information on the neonates were prospectively recorded.
Ultrasonography
Ultrasonography was performed using an Acuson Sequoia 512 (Mountainview, CA, USA) system with a 2.5–6 MHz curvilinear transducer. After a survey of fetal anatomy, biometry was performed to exclude intrauterine growth restriction, and the placental circulation was assessed using Doppler. Blood flow velocity waveforms were obtained from the umbilical artery and maternal uterine arteries, and the pulsatility index was calculated (Gosling et al., 1971). Umbilical vein velocity and diameter were measured and the volume blood flow was calculated as described previously (Acharya et al., 2005).
Sample collection and conservation
Chorionic tissue was dissected from a standardized location (
2 cm beside the umbilical cord insertion, from the middle layer of placenta midway between maternal and fetal surfaces) by two designated persons (V.S. and Å.V.) in order to reduce the bias related to the physiological difference in gene expression within the same placenta depending on the sampling site (Sood et al., 2006). The collected specimen (2 cm3) was transferred to a Petri dish and washed thoroughly with physiological saline to remove any contamination with maternal blood and amniotic fluid. Each tissue sample was cut in two pieces and transferred to tubes containing 1.5 ml RNAlater solution (RNA stabilization reagent, Qiagen GmbH, Germany), and stored at –70°C until RNA isolation, microarray and reverse transcription polymerase chain reaction (RT-PCR).
RNA isolation and quality/quantity control
Disruption and homogenization of tissue specimens were performed in lysis buffer using the MagNa Lyser instrument (Roche Applied Science, Germany), according to the manufacturer's instructions. Isolation of total RNA was performed using the MagNa Pure Compact RNA isolation kit and the MagNa Pure Compact instrument (Roche Applied Science, Germany) (Paulssen et al., 2006). RNA was quantified by measuring absorbance at 260 nm, and RNA purity was determined by the ratios OD260 nm/280 nm and OD230 nm/280 nm using the NanoDrop instrument (NanoDrop® ND-1000, Wilmington, USA). The RNA integrity was determined by electrophoresis using the Agilent 2100 Bioanalyser (Matriks, Norway). RNA samples with RNA Integrity Number >7.2 were used for microarray.
Microarray procedures
For global gene expression analysis, we used 35 K oligo-microarrays that were obtained from the Norwegian Microarray Consortium (http://www.microarray.no). Briefly, the arrays contained spotted 70-mer oligonucleotides obtained from the Human Array-Ready Oligo Sets (AROSTM) v3.0, OPERON, Germany (http://www.operon.com). The set contains 34 580 probes representing 24 650 human genes and 37 123 gene transcripts. The probe design is fully based on the Ensembl Human 13.31 Database (http://www.ensembl.org) and Human Genome Sequencing Project. As an external control system, the Spot Report oligo validation system (Cat # 252170–7) from Stratagene was used.
Total RNA was reverse transcribed and labelled with Cy3- and Cy5-attached dendrimer, using the Genisphere 3DNA 350HS kit (Genisphere, Montvale, NJ, USA) as described in the manufacturer's protocol. Hybridizations were carried out in a TECAN HS4800 instrument (TECAN, Austria) using the formamide-based hybridization buffer from Genisphere containing 5% dextrane sulphate and 5.5 ng/ml human COT1-DNA (GIBCO-BRL Life technologies) at 37° for 23 h. Three DNA dendrimer hybridizations were carried out in formamide-based hybridization buffer alone. Post-hybridization washes were carried out at room temperature with 2 x saline sodiumcitrate (SSC) for 1 min, 0.2% sodium dodecylsulphate (SDS)/2 x SSC for 1 min and finally with 0.2 x SSC for 30 s. The arrays were scanned with the GenePix 4000B scanner (Axon Instruments Inc, 2004).
Experimental design
Of 27 placentas obtained from labouring women, 17 were randomly selected to match with 17 placentas obtained from non-labouring women and the microarrays were performed by applying a direct comparison design.
Data analysis
The features were extracted from the arrays using Genepix 6.0 software (Axon instruments Inc., 2004). The background estimates were calculated using the morphological opening method (Soille, 2006). Spots that displayed a signal-to-noise ratio of less than three or that were significantly saturated (more than 20% saturation among foreground pixels) were filtered out. The median was used as the averaging measure of the foreground pixels. After quality control, genes that were present in less than 50% of the arrays were filtered out. Normalization was carried out using Lowess normalization (Cleveland, 1979). The sample labelling was balanced across the groups, presumably attenuating any dye-effect. For the purpose of finding differentially expressed genes, we applied an empirical Bayes analysis (Smyth, 2004) using the LIMMA package (Smyth, 2000). This involves using a t-statistic whose standard error component has been pooled across all other gene standard error estimates. This gives more degrees of freedom with which to make statistical inference, and produces more stable standard error estimates. The data were analysed using a two-component linear model. The prior guess of the number of differentially expressed genes was set to 0.01. Multiple testing was accounted for by estimating the false discovery rate (set at <15–20%) applying the Benjamini–Hochberg (Benjamini, 1995) and Storeys less conservative Q-value (Storey, 2002) procedure. A 2.5-fold change in expression of any gene that was present on 
8 arrays was considered significant, if the difference in fluorescence intensity between two matched samples reached a P-value of <0.01.
Database submission of microarray data
The microarray data were prepared according to minimum information about microarray experiment (MIAME) recommendations (Brazma et al., 2001) and deposited in the Gene Expression Omnibus (GEO) database: http://www.ncbi.nlm.nih.gov/geo/. The GEO accession number for the platform is GPL4790
[NCBI GEO]
. The 17 arrays can be retrieved with GEO accession number GSM207427
[NCBI GEO]
–GSM207443 and the series can be constituted with GEO accession number GSE8375
[NCBI GEO]
.
Annotations
We used PubGene 2.6TM Database and Analysis Software (Jenssen et al., 2001) and DAVID Bioinformatics Resources 2007 (Dennis et al., 2003) for annotations of the genes.
Validation of microarray results by RT-PCR
Total RNA from labouring and non-labouring placentas were reverse transcribed using Transcriptor First Strand cDNA Synthesis Kit (Roche Applied Science, Germany) as described by the manufacturer's protocol. TaqMan RT-PCR amplification was performed with an ABI HT7900 Instrument (Applied Biosystems) using primers and probes designed with the Universal Probe Library (Roche Applied Science, Germany). The following primers and probes have been used: GAPDH-fw, 5'-GCCCAATACGACCAAATCC-3', GAPDH-rev, 5'-AGCCACATCGCTCAGACAC-3', GAPDH probe #60; SDHA-fw, 5'-CGTAGAAATGCCACCTCCA-3', SDHA-rev, 5'-ACCAGGTCACACACTGTTGC-3', SDHA probe #25; LRAP-fw, 5'-CAAAACCCTCCTTAAGCCAAA-3', LRAP-rev, 5'-GAGTCATAGCCCATGAACTGG-3', LRAP probe #31; HSD17B4-fw, 5'-GAGGGAGTTTCTGGCCAAT-3', HSD17B4-rev, 5'-AGTCGTGCAACGTCTACAGC-3', HSD17B4 probe #67; FOS-fw, 5'-AGGTCCGTGCAGAAGTCCT-3', FOS-rev, 5'-CTACCACTCACCCGCAGACT-3', FOS probe #67; FOSB-fw, 5'-TCCTCCAACTGATCTGTCTCC-3', FOSB-rev, 5'-AGCAGCTAAATGCAGGAACC-3', FOSB probe #24. Samples for each experiment were run in duplicate or triplicate and averaged for final quantification. The fold inductions were calculated as described previously (Livak and Schmittgen, 2001).
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Results |
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Of a total of 50 participants recruited to the study, 17 had elective Caesarean section before the onset of labour (non-labouring). The indications were breech presentation (n = 7), previous Caesarean section (n = 7), placenta paevia (n = 2) and cephalo-pelvic disproportion (1). Among 33 labouring women, 27 had a vaginal delivery (24 normal deliveries and 3 vacuum deliveries). The remaining six who delivered by emergency Caesarean section after the onset of labour (two due to fetal distress, four due to prolonged labour) were excluded from the study. Baseline characteristics and pregnancy outcomes of the women included in the microarray analysis are summarized in Table I. There were no significant differences between the labouring and non-labouring groups.
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We found that in labouring placentas 92 genes were down-regulated and 94 genes were up-regulated compared to non-labouring placentas. However, none of these genes was differentially expressed at a significant level (Fig. 1). The onset of labour was spontaneous in all but six women who delivered vaginally. Excluding the arrays from placentas obtained after induced labour did not alter the result of data analysis.
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Only one gene, V-fos murine osteosarcoma viral oncogene homolog (FOS), was down-regulated 2.5-fold and was present in 16 out of 17 arrays (P = 0.0001). Two other genes were down-regulated more than 2-fold, namely: FBJ murine osteosarcoma viral oncogene homolog B (FOSB) (2.02-fold, P = 0.006, present on 11 arrays) and Guanidine nucleotide binding protein (G protein), gamma transducing activity polypeptide 1 (GNGT1) (2.04-fold, P = 1.14E–05, present in all 17 arrays).
Data analysis confirmed that several other differentially expressed genes resulting from our data analysis are expressed in placenta and are involved in hormone metabolism. We chose two of these genes, i.e. leukocyte-derived arginine amino peptidase (LRAP) (1.21-fold, P = 0.03, present on 11 arrays) and hydroxysteroid (17-beta) dehydrogenase 4 (HSD17B4) (1.28-fold, P = 0.02, present on nine arrays) together with FOS and FOSB in order to validate our results by semi-quantitative RT-PCR (Table II).
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Discussion |
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Labour remains a clinical diagnosis and its physiology is still incompletely understood. Elucidating mechanisms that control the duration of pregnancy and initiation of labour would help clinicians to diagnose and prevent preterm labour and reduce the perinatal morbidity associated with preterm and posterm delivery. We performed microarray on near term human placenta from labouring and non-labouring women with uncomplicated pregnancies in order to investigate the effect of labour on global gene expression profile. To our knowledge, this is the first study to address this question. We found several genes involved in placental hormone metabolism to be up- or down-regulated, however, none of these was differentially expressed at a significant level.
More specifically, we found that FOS, FOSB and GNGT1 were down-regulated (2- to 2.5-fold) in labouring placentas suggesting that these genes could have been affected by labour. The FOS gene family consists of four members: FOS, FOSB, FOSL1 and FOSL2. Together with the JUN gene family they are called ‘primary response genes' because they can be activated without intervening protein synthesis. FOS genes encode leucine zipper proteins that can dimerize with proteins of the JUN family, thereby forming the transcription factor complex AP-1. Fos proteins have been implicated as regulators of cell proliferation, differentiation and transformation. FOS expression can be increased by a variety of stimuli including growth factors, cytokines, neurotransmitters, polypeptide hormones, stress and cell injury (Lin et al., 1998). There are several reports indicating that FOS and FOSB co-expression are involved in neural activation during parturition, lactation and maternal behaviour in rats (Antonijevic et al., 1995; Roh, 1999). Our findings suggest that the FOS gene family maybe involved in preparing the feto-placental unit for labour towards the end of pregnancy but are not significantly affected by the parturition process itself. GNGT1 encodes the gamma 1 subunit of heterotrimeric G protein (transducin) thought to be specific to rod photoreceptors in retina. Although it is expressed in human placenta (http://www.dsi.univ-paris5.fr/genatlas/fiche.php?symbol = GNGT1), its function has not been investigated.
The LRAP and HSD17B4 genes that encode respective enzymes were up-regulated in labouring placentas. The LRAP enzyme, together with placental leucine amino peptidase (LNPEP) and adipocyte-derived leucine amino peptidase (A-LAP) constitute the M1 subfamily of amino peptidases, also called 'Oxytocinases' (Yamahara et al., 2000; Kozaki et al., 2001; Tsujimoto and Hattori, 2005). Their function is to degrade oxytocin (Kiss and Mikkelsen, 2005) and thus play an important role in the maintenance of pregnancy. Serum levels of oxytocinases are known to increase during gestation and reach a maximum near term. The HSD17B4 gene encodes an enzyme that plays an important role in the inactivation of estrogens (Labrie et al., 1997). Expression of contraction-associated proteins is promoted by estrogen and inhibited by progesterone. In primates, the placenta is responsible for the metabolism of estrogen after aromatization of precursors produced by the fetal adrenals (Miller, 1998; Thornton et al., 1999; Challis et al., 2000a, b).
Despite these possible roles, the results of our study, generally suggest that the gene expression profile in placenta is not significantly affected by the process of labour itself. The stringent criteria used for the interpretation of microarray data analysis regarding differential gene expression could be one of the reasons for this predominantly negative finding. However, the phenotypic homogeneity of our study population strongly suggests that any differences in placental gene expression are due to the effect of labour and not due to other confounding factors. Moreover, the cervix and the myometrium are considered to be the key response tissues in parturition (Challis et al., 2000b; Young, 2007), rather than the placenta. Most probably, a cross talk between the fetus, placenta and mother is involved in the timing of labour and there is compelling evidence that the fetus is in control of this timing (Snegovskikh et al., 2006). The starting point of the cascade of parturition is the activation of the fetal hypothalamic-pituitary-adrenal axis. Experimental studies in non-human primates have shown that the removal of the fetus, leaving the placenta behind, results in prolongation of pregnancy, indicating that the placenta has only a secondary or intermediary role in the mechanisms of initiation of labour (Nathanielsz et al., 1992).
For the microarray experiments, we applied a direct comparison design, i.e. measured the fluorescence intensity of cDNA from one labouring versus one non-labouring placenta hybridized to the oligonucleotides spotted on each array. It has a higher precision compared to an indirect design, i.e. hybridizing each labouring placenta with the same common reference (pooled RNA from all non-labouring placentas), because the replicates available for comparison are doubled in number. Additionally, due to instability in the common reference, the between-slide variation is generally more than the within-slide variation. Therefore, a direct design is likely to provide a more accurate comparison between samples.
It is conceivable that the maturational changes in the placenta that occur throughout the gestation are reflected in the gene expression profile. However, our study was not designed to investigate the effect of gestational age on the placental gene expression profile. The control placentas were obtained at elective Caesarean section before the onset of labour but after 38 weeks. It is likely that the changes that occur in the feto-placental unit in preparation for labour are already complete by that time. Therefore, from the results of this study we are unable to infer any information on the effect of preterm labour on the placental gene expression profile.
In summary, gene expression in the near term placenta is not significantly altered by labour, suggesting that the mode of delivery has no major implication in the interpretation of results of genomic studies on placenta.
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Funding |
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Faculty of Medicine, University of Tromsø and Northern Norway Regional Health Authority (grant number: 721484).
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Acknowledgements |
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We thank Thea Charlotte Sogn and Jørn Leirvik from the Microarray Resource Centre Tromsø (MRCT) (www.unn.no/labforum) for superb technical assistance. We would like to thank Professor Jan Martin Maltau for his valuable input during the planning of this project. We acknowledge the Norwegian Microarray Consortium (NMC) for providing the microarrays (www.mikroamtrise.no). Preliminary results of this study were presented at the 27th Annual Meeting of the Society for Maternal-Fetal Medicine, San Francisco, USA.
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Footnotes |
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These authors contributed equally to this work. 
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Submitted on September 14, 2007; resubmitted on November 8, 2007; accepted on November 27, 2007.
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