Trophoblast stem cell-based organoid models of the human placental barrier.

Human placental villi have essential roles in producing hormones, mediating nutrient and waste exchange, and protecting the fetus from exposure to xenobiotics. Human trophoblast organoids that recapitulate the structure of villi could provide an important in vitro tool to understand placental development and the transplacental passage of xenobiotics. However, such organoids do not currently exist. Here we describe the generation of trophoblast organoids using human trophoblast stem (TS) cells. Following treatment with three kinds of culture medium, TS cells form spherical organoids with a single outer layer of syncytiotrophoblast (ST) cells that display a barrier function. Furthermore, we develop a column-type ST barrier model based on the culture condition of the trophoblast organoids. The bottom membrane of the column is almost entirely covered with syndecan 1-positive ST cells. The barrier integrity and maturation levels of the model are confirmed by measuring transepithelial/transendothelial electrical resistance (TEER) and the amount of human chorionic gonadotropin. Further analysis reveals that the model can be used to derive the apparent permeability coefficients of model compounds. In addition to providing a suite of tools for the study of placental development, our trophoblast models allow the evaluation of compound transfer and toxicity, which will facilitate drug development.

CRISPR screening in human trophoblast stem cells reveals both shared and distinct aspects of human and mouse placental development.

The placenta serves as the interface between the mother and fetus, facilitating the exchange of gases and nutrients between their separate blood circulation systems. Trophoblasts in the placenta play a central role in this process. Our current understanding of mammalian trophoblast development relies largely on mouse models. However, given the diversification of mammalian placentas, findings from the mouse placenta cannot be readily extrapolated to other mammalian species, including humans. To fill this knowledge gap, we performed CRISPR knockout screening in human trophoblast stem cells (hTSCs). We targeted genes essential for mouse placental development and identified more than 100 genes as critical regulators in both human hTSCs and mouse placentas. Among them, we further characterized in detail two transcription factors, DLX3 and GCM1, and revealed their essential roles in hTSC differentiation. Moreover, a gene function-based comparison between human and mouse trophoblast subtypes suggests that their relationship may differ significantly from previous assumptions based on tissue localization or cellular function. Notably, our data reveal that hTSCs may not be analogous to mouse TSCs or the extraembryonic ectoderm (ExE) in which in vivo TSCs reside. Instead, hTSCs may be analogous to progenitor cells in the mouse ectoplacental cone and chorion. This finding is consistent with the absence of ExE-like structures during human placental development. Our data not only deepen our understanding of human trophoblast development but also facilitate cross-species comparison of mammalian placentas.

Variation of DNA methylation on the IRX1/2 genes is responsible for the neural differentiation propensity in human induced pluripotent stem cells.

Introduction: Human induced pluripotent stem cells (hiPSCs) are useful tools for reproducing neural development in vitro. However, each hiPSC line has a different ability to differentiate into specific lineages, known as differentiation propensity, resulting in reduced reproducibility and increased time and funding requirements for research. To overcome this issue, we searched for predictive signatures of neural differentiation propensity of hiPSCs focusing on DNA methylation, which is the main modulator of cellular properties. Methods: We obtained 32 hiPSC lines and their comprehensive DNA methylation data using the Infinium MethylationEPIC BeadChip. To assess the neural differentiation efficiency of these hiPSCs, we measured the percentage of neural stem cells on day 7 of induction. Using the DNA methylation data of undifferentiated hiPSCs and their measured differentiation efficiency into neural stem cells as the set of data, and HSIC Lasso, a machine learning-based nonlinear feature selection method, we attempted to identify neural differentiation-associated differentially methylated sites. Results: Epigenome-wide unsupervised clustering cannot distinguish hiPSCs with varying differentiation efficiencies. In contrast, HSIC Lasso identified 62 CpG sites that could explain the neural differentiation efficiency of hiPSCs. Features selected by HSIC Lasso were particularly enriched within 3 Mbp of chromosome 5, harboring IRX1, IRX2, and C5orf38 genes. Within this region, DNA methylation rates were correlated with neural differentiation efficiency and were negatively correlated with gene expression of the IRX1/2 genes, particularly in female hiPSCs. In addition, forced expression of the IRX1/2 impaired the neural differentiation ability of hiPSCs in both sexes. Conclusion: We for the first time showed that the DNA methylation state of the IRX1/2 genes of hiPSCs is a predictive biomarker of their potential for neural differentiation. The predictive markers for neural differentiation efficiency identified in this study may be useful for the selection of suitable undifferentiated hiPSCs prior to differentiation induction.

Identification of an epigenetic signature in human induced pluripotent stem cells using a linear machine learning model.

The use of human induced pluripotent stem cells (iPSCs), used as an alternative to human embryonic stem cells (ESCs), is a potential solution to challenges, such as immune rejection, and does not involve the ethical issues concerning the use of ESCs in regenerative medicine, thereby enabling developments in biological research. However, comparative analyses from previous studies have not indicated any specific feature that distinguishes iPSCs from ESCs. Therefore, in this study, we established a linear classification-based learning model to distinguish among ESCs, iPSCs, embryonal carcinoma cells (ECCs), and somatic cells on the basis of their DNA methylation profiles. The highest accuracy achieved by the learned models in identifying the cell type was 94.23%. In addition, the epigenetic signature of iPSCs, which is distinct from that of ESCs, was identified by component analysis of the learned models. The iPSC-specific regions with methylation fluctuations were abundant on chromosomes 7, 8, 12, and 22. The method developed in this study can be utilized with comprehensive data and widely applied to many aspects of molecular biology research.

Dog Steroidogenic Factor-1: Molecular cloning and analysis of epigenetic regulation.

Steroidogenic factor 1 (SF-1) is a nuclear receptor that is important in steroid hormone production, and adrenal and gonad development. The SF-1 gene is highly conserved among most vertebrates. However, dog SF-1 registered in public databases, such as CanFam3.1, lacks the 5' end compared to other mammals including mouse, human, bovine, and cat. Whether this defect is due to species differences or database error is unclear. Here, we determined the full-length dog SF-1 cDNA sequence and identified the missing 5' end sequence in the databases. The coding region of the dog SF-1 gene has 1,386 base pairs, and the protein has 461 amino acid residues. Sequence alignment analysis among vertebrates revealed that the 5' end sequence of dog SF-1 cDNA is highly conserved compared to other vertebrates. The genomic position of the first exon was determined, and its promoter region sequence was analyzed. The DNA methylation state at the basal promoter and the expression of dog SF-1 in steroidogenic tissues and non-steroidogenic cells were examined. CpG sites at the basal promoter displayed methylation kinetics inversely correlated with gene expression. The promoter was hypomethylated and hypermethylated in SF-1 expressing and non-SF-1 expressing tissues, respectively. In conclusion, we identified the true full sequence of dog SF-1 cDNA and determined the genome sequence around the first exon. The gene is under the control of epigenetic regulation, such as DNA methylation, at the promoter.