[1S06e] 15. Advanced Cell and Cell Culture Engineering for Biopharmaceuticals and Functional Food - Part 3

5:50 PM - 6:10 PM JST(8:50 AM - 9:10 AM UTC)

[1ACCE-14] A functional prediction system for food and medicinal resources using human amniotic epithelial-derived pluripotent stem cells

○Hiroko Isoda¹ (1. University of Tsukuba (Japan))

Keywords:

food and medicinal resources,functionality,prediction model,multi potentiate stem cells,human amniotic stem cell

We are promoting a distinctive research strategy that utilizes a three-dimensional (3D) spheroid culture system based on human amniotic stem cells as pluripotent stem cells. In recent years, human amniotic epithelial cells (hAECs), which are stem cells derived from the amniotic membrane forming the innermost layer of the fetal membranes, have attracted considerable attention as a safe and effective source of stem cells.Compared with other stem cell types, hAECs possess several notable advantages. Most importantly, hAECs originate from the pluripotent epiblast and therefore retain multilineage differentiation potential comparable to that of embryonic stem cells. Under appropriate differentiation protocols, hAECs have been shown to differentiate into a wide range of cell types, including endoderm-derived hepatocytes, pancreatic cells, and pulmonary epithelial cells; mesoderm-derived osteocytes, adipocytes, and cardiomyocytes; and ectoderm-derived neural cells. In addition, hAECs are non-tumorigenic, exhibit low immunogenicity, and display strong immunomodulatory properties, presenting a mesenchymal stem cell (MSC)-like phenotype.Our research focuses on bioactive compounds derived from Mediterranean food and medicinal resources with traditional pharmacological properties. Using hAECs, we integrate whole-genome transcriptome analyses with mechanistic studies conducted in functional differentiated cells and disease model mice, while mutually validating the obtained datasets. Based on these accumulated data, we are developing a machine learning–based system for predicting biological functions of natural compounds.The potential of this functional prediction platform, which leverages extensive genomic information obtained from 3D spheroid-cultured hAECs, is substantial. This approach enables accurate reflection of biological responsiveness and is expected to markedly enhance research efficiency by allowing functional prediction without relying on numerous individual experimental evaluation systems. Furthermore, the established platform technology is applicable to the prediction of other biological functions and the discovery of highly functional molecules from food and medicinal resources.Elucidation of their mechanisms of action may contribute not only to the development of foods with health claims, but also to the creation of medicinal cosmetics and healthcare products, thereby supporting the generation of diverse and sustainable industries.We propose that the use of food- and medicinal resource–derived components in regulating stem cell proliferation and lineage-specific differentiation, combined with bioinformatics-based analytical approaches, enables the development of a novel research framework. This strategy facilitates systematic evaluation of bioactive compounds and advances our understanding of their mechanisms of action, thereby contributing to the establishment of innovative platforms for stem cell biology and functional compound discovery.