Associate Professor Viljar Jaks, University of Tartu
Professor Andres Salumets, University of Tartu
Associate Professor Kaarel Krjutškov, University of Tartu
Doctor Kalle Rytkönen, Institute of Biomedicine, Turku Center of Biosciences (Finland)
Embryo implantation is a complex process in human reproduction, requiring precise coordination between maternal cells and the developing embryo. The receptive state of the endometrium, known as the "window of implantation," is crucial for successful embryo attachment. Despite the naturalness of pregnancy, infertility remains a significant challenge for many couples. Ethical limitations on in vivo studies hinder a comprehensive understanding of the implantation process, requiring alternative approaches. This doctoral thesis investigates the molecular communication between endometrial cells and embryonic trophoblasts. It elucidates the maturation process of the female endometrial tissue and its correlation with changes in gene expression patterns in the two primary types of endometrial cells: stromal and epithelial cells. Drawing from this study, a novel method for analyzing gene activity was developed to determine the levels of crucial RNA molecules associated with endometrial receptivity to identify the optimal timing for embryo transfer in women undergoing infertility treatment. Based on cell type-specific gene expression data, approximately 550 protein-protein interactions were characterized, forming a molecular network between the embryo and endometrial cells essential for initiating new life. Additionally, proper placenta development is crucial for a successful pregnancy, relying on trophoblast cell differentiation to support fetal growth and function. The thesis explores techniques to differentiate human embryonic stem cells into trophoblast-like cells, targeting the BMP4 signaling pathway while inhibiting TGFβ and FGF2 pathways crucial for placental formation. The knowledge generated through this research contributes to future advancements in reproductive research. It opens new possibilities for improving embryo transfer success rates and provides insights for developing prognostic and diagnostic biomarkers for infertility diagnosis and treatment optimization.