CSIRO PUBLISHING Reproduction, Fertility and Development http://dx.doi.org/10.1071/RD15077 Genomic expression profiles in cumulus cells derived from germinal vesicle and MII mouse oocytes Li ShaoA, Ri-Cheng ChianA,B,C, Yixin XuA, Zhengjie YanA, Yihui ZhangA, Chao GaoA, Li GaoA, Jiayin LiuA and Yugui CuiA,C AState Key Laboratory of Reproductive Medicine, Center for Clinical Reproductive Medicine, First Affiliated Hospital, Nanjing Medical University, 140 Hanzhong Road, Nanjing 210029, China. BDepartment of Obstetrics and Gynecology, McGill University, 687 Pine Avenue West, Montreal H3A 1A1, Canada. CCorresponding authors. Emails: [email protected]; [email protected] Abstract. Cumulus cells (CCs) are distinct from other granulosa cells and the mutual communication between CCs and oocytes is essential for the establishment of oocyte competence. In the present study we assessed genomic expression profiles in mouse CCs before and after oocyte maturation in vitro. Microarray analysis revealed significant changes in gene expression in CCs between the germinal vesicle (GV) and metaphase II (MII) stages, with 2615 upregulated and 2808 downregulated genes. Genes related to epidermal growth factor, extracellular matrix (Ptgs2, Ereg, Tnfaip6 and Efemp1), mitochondrial metabolism (Fdx1 and Aifm2), gap junctions and the cell cycle (Gja1, Gja4, Ccnd2, Ccna2 and Ccnb2) were highlighted as being differentially expressed between the two development stages. Real-time polymerase chain reaction confirmed the validity and reproducibility of the results for the selected differentially expressed genes. Similar expression patterns were identified by western blot analysis for some functional proteins, including EFEMP1, FDX1, GJA1 and CCND2, followed by immunofluorescence localisation. These genes may be potential biomarkers for oocyte develop- mental competence following fertilisation and will be investigated further in future studies. Additional keywords: biomarkers, developmental competence, in vitro maturation. Received 25 February 2015, accepted 21 April 2015, published online 20 May 2015 Introduction potential on the basis of gene expression profiles of human CCs, The cumulus–oocyte complex (COC) comprises a secondary Assou et al. (2008) found that there was a correlation between oocyte surrounded by a subgroup of distinctive somatic cells, the expression of some genes in CCs and embryo potential or namely cumulus cells (CCs). It has been widely accepted that pregnancy outcome, and proposed BCL2 L11, PCK1 and NFIB CCs maintain an intimate relationship with the oocyte through as biomarkers for predicting pregnancy. Interestingly, a recent gap junctions and paracrine signalling during folliculogenesis report indicated that there were significant differences in the (Su et al. 2004; Gilchrist et al. 2008). Following the LH surge, expression of SPSB2 and TP5313 between CCs of normal and communication between the oocyte and CCs induces oocyte chromosomally abnormal oocytes (Fragouli et al. 2012). maturation, because CCs compensate for oocyte-deficient It has been reported that gene expression differs between CCs metabolic molecules, such as pyruvate, alanine and cholesterol, associated with oocytes at the metaphase II (MII) stage com- to support oocyte development. Meanwhile, the oocyte secrets a pared with those at the germinal vesicle (GV) and metaphase I series of paracrine factors, such as growth differentiation factor (MI) stages, suggesting that the gene expression profile of CCs 9 (GDF9), bone morphogenetic protein 15 (BMP15) and of the mature MII oocyte may be used as a predictor of oocyte fibroblast growth factor 8 (FGF8), which act on adjacent CCs to quality(Ouandaogo et al. 2011). Furthermore, when comparing promote proliferation and differentiation (Gilchrist et al. 2008; the transcriptome profiles of CCs from in vivo- and in vitro- Su et al. 2009). matured human COCs at different nuclear maturation stages, Previous studies have used microarray analysis and real-time Ouandaogo et al. (2012) found that the transcriptomic signature polymerase chain reaction (PCR) to focus on gene expression of the CCs varies according to both oocyte maturation stages and profiles in granulosa cells (GCs) or CCs in an effort to find the maturation conditions, and suggested that there was a delay potential biomarkers of oocyte quality (Assou et al. 2006, 2010; in the acquisition of the mature CC phenotype following in vitro Patrizio et al. 2007; Huang and Wells 2010; Assidi et al. 2011; maturation (IVM). Therefore, it seems likely that screening for Vigone et al. 2013). Using a non-invasive test to assess embryo changes in gene expression in CCs under different maturation Journal compilation Ó CSIRO 2015 www.publish.csiro.au/journals/rfd B Reproduction, Fertility and Development L. Shao et al. conditions would make it possible to optimise the in vitro culture combined with mechanical isolation by pipetting. CCs were system (Kind et al. 2013; Salhab et al. 2013). However, only grouped according to the relevant oocyte maturation stage, limited data are available regarding gene expression profiles of which were evaluated under a stereomicroscope. Oocytes with a CCs in association with oocyte maturation. GV in the ooplasm were defined as being at the GV stage, IVM can imitate in vivo progress of oocyte maturation, which whereas oocytes with a first polar body in the perivitelline space is a good model to find some biomarkers during oocyte matura- were defined as being at the MII stage. CCs were washed in cold tion in CCs, and to understand the molecular mechanisms of the phosphate-buffered saline (PBS) before being centrifuged at mutual communication between two kinds of cells. It is neces- 300g for 10 min at 378C. The supernatant was discarded and the sary to clarify the molecular mechanism of oocyte maturation pellet was resuspended in Trizol reagent (Invitrogen, Waltham, during IVM in order to optimise the culture system and to obtain MA, USA) before being stored at À808C until microarray high developmental potential oocytes for clinical outcomes. The analysis. CCs from more than 100 COCs were pooled together objective of this study was to compare the differences of as one sample; each group contained at least three independent genomic expression profiles in CCs before and after IVM and pooled samples for microarray analysis. was to try to find some potential target genes expressed in CCs for further study of oocyte developmental competence. Total RNA extraction and microarray analysis Materials and methods Total RNA was extracted from pooled CC samples (three each Animal preparation from the GV-CCs and MII-CCs groups) as described previ- ously (Dai et al. 2014) and was isolated using an RNeasy Mini Three-week-old ICR mice were obtained from the Medical Kit (7410; Qiagen, Valencia, CA, USA) according to the Experimental Animal Center of Nanjing Medical University and manufacturer’s instructions. The quality of the RNA was maintained at 20–228C under a 12-h light–dark cycle. Sterilised confirmed using a NanoDrop ND-1000 spectrophotometer food and water were provided ad libitum. Animal experiments (Thermo Scientific, Waltham, MA, USA). The microarray were conducted in accordance with the Animal Research analysis was performed on an Agilent Technologies (Santa Committee Guidelines of Nanjing Medical University, which Clara, CA, USA) array platform (Whole Mouse Genome Oligo were approved by the Animal and Human Ethics Board of Microarray). Briefly, total RNA from each sample was Nanjing Medical University. amplifiedlinearlyandlabelledwithCy3-UTPusingthe Agilent One-Colour Quick Amp Labelling Kit, resulting in Ovarian stimulation, COC collection and IVM labelled cRNAs. The labelled cRNAs were then purified using Mice were injected with 5 IU, i.p., equine chorionic gonado- the RNasey Mini Kit and the corresponding concentration and tropin (eCG; Folligon; Intervet, Castle Hill, NSW, Australia) to specific activity (pmol Cy3 per mgcRNA)wereassessed stimulate follicle development. Then, 46–48 h after eCG injec- using the NanoDrop ND-1000 spectrophotometer. Next, a 1-mg tion, mice were killed by cervical dislocation and the ovaries aliquot of each labelled cRNA was fragmented, followed by dissected out and placed in M2 medium (M716; Sigma, St Louis, hybridisation to the Mouse 4x44K Genome Oligo Microarray MO, USA). Immature COCs were released by puncturing the (Agilent Technologies), which contained 39 000þ mouse ovarian surface with a sterile 27-G needle and collected using genes and transcripts, using Agilent’s 60-mer SurePrint tech- Pasteur micropipettes; only those with a compacted cumulus nology. After hybridisation, the arrays were washed, fixed and were selected for use in the present study. COCs from each scanned using an Agilent G2505C scanner. mouse were randomly divided into two groups, the first to be For analysis of microarray data, the array images were used immediately (GV-CCs group) and second to be used for extracted using Agilent Feature Extraction software (version IVM (MII-CCs group). COCs in the latter group were washed 11.0.1.1). Raw signal intensity data were quintile normalised twice with IVM medium and then groups of 10 COCs were place and subsequently processed using GeneSpring GX v12.0 m in 30- L droplets of IVM medium (see Zhang et al. 2014) (Agilent Technologies). After quintile normalisation, genes covered by mineral oil (MKBG7544V; Sigma) and then cul- for which at least three of six samples were flagged as ‘Detected’ 8 tured