Integration of parallel metabolomics and transcriptomics reveals metabolic patterns in porcine oocytes during maturation

Combined analysis of temporal metabolomics and transcriptomics reveals the metabolic patterns in goat oocytes during maturation

Well-balanced and orderly metabolism is a crucial prerequisite for promoting oogenesis. Involvement of single metabolites in oocyte development has been widely reported; however, the comprehensive metabolic framework controlling oocyte maturation is still lacking. In the present study, we employed an integrated temporal metabolomic and transcriptomic method to analyze metabolism in goat oocytes at GV, GVBD, and MII stages (GV, fully-grown immature oocyte; GVBD, stage of meiotic resumption; MII, mature oocyte) during in vitro maturation, revealing the global picture of the metabolic patterns during maturation. In particular, several significantly altered metabolic pathways during goat oocyte meiosis have been identified, including active serine metabolism, increased utilization of tryptophan, and marked accumulation of purine nucleotide. In summary, the current study provides transcriptomic and metabolomic datasets for goat oocyte development that can be applied in cross-species comparative studies.

Maturation and culture affect the metabolomic profile of oocytes and follicular cells in young and old mares

Introduction: Oocytes and follicular somatic cells within the ovarian follicle are altered during maturation and after exposure to culture in vitro. In the present study, we used a nontargeted metabolomics approach to assess changes in oocytes, cumulus cells, and granulosa cells from dominant, follicular-phase follicles in young and old mares. Methods: Samples were collected at three stages associated with oocyte maturation: (1) GV, germinal vesicle stage, prior to the induction of follicle/oocyte maturation in vivo; (2) MI, metaphase I, maturing, collected 24 h after induction of maturation in vivo; and (3) MIIC, metaphase II, mature with collection 24 h after induction of maturation in vivo plus 18 h of culture in vitro. Samples were analyzed using gas and liquid chromatography coupled to mass spectrometry only when all three stages of a specific cell type were obtained from the same mare. Results and Discussion: Significant differences in metabolite abundance were most often associated with MIIC, with some of the differences appearing to be linked to the final stage of maturation and others to exposure to culture medium. While differences occurred for many metabolite groups, some of the most notable were detected for energy and lipid metabolism and amino acid abundance. The study demonstrated that metabolomics has potential to aid in optimizing culture methods and evaluating cell culture additives to support differences in COCs associated with maternal factors.