stem-cell–based-embryo-models-reveal-pathway-to-understanding-fertility

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Caltech scientists have devised an innovative method for generating embryo-like formations from stem cells that could revolutionize our approach to studying fertility.

Instead of utilizing a conventional fertilized egg, the group has created mouse embryo models known as iG4-blastoids that closely replicate natural blastocysts, which is the phase of development when an embryo embeds itself into the uterus. This implantation phase is when most pregnancies falter, including those achieved through in vitro fertilization, and there is limited understanding regarding the reasons. The new models will allow researchers to investigate the influence of environmental elements, such as exposure to caffeine, nicotine, alcohol, and dietary habits.

The study was spearheaded by the lab of Magdalena Zernicka-Goetz, Bren Professor of Biology and Biological Engineering at Caltech, and is detailed in a publication featured in the journal Developmental Cell.

“This model has the potential to transform fertility research—illuminating the reasons some pregnancies fail and how to enhance the ones that do succeed,” Zernicka-Goetz states. “These living models permit us to observe, in a dish, how early embryos arrange themselves, and to investigate how prevalent environmental exposures—like caffeine, alcohol, nicotine, and even high or low protein diets—affect that process.”

The research team discovered that iG4-blastoids reacted to toxins and shifts in nutrients similarly to natural embryos. For instance, caffeine and nicotine during the early stages of pregnancy decreased cell counts and hindered development, while changes in amino acid availability replicated the effects of high- or low-protein diets on embryo advancement.

The researchers constructed the iG4-blastoids using three distinct types of stem cells, one of which was engineered to express a crucial developmental gene (GATA4). The expression of GATA4 marked a significant breakthrough after other attempts at generating stem-cell-derived blastoids were unsuccessful. Notably, the method produces well-developed blastoids 80 percent of the time. This high effectiveness allows the researchers to generate thousands of models and carry out thorough experiments; for instance, testing the effects of caffeine on specific developmental days or examining the impact of varying concentrations at different intervals.

Although this investigation was conducted in mice, the models will greatly improve our understanding of the fundamental biological processes that underlie reproduction, such as the reasons preventing otherwise genetically sound embryos from implanting—a pivotal milestone in development—and the mechanisms explaining why certain environmental factors may hinder progress.

“This technique represents a paradigm shift,” asserts Sergi Junyent, a Caltech postdoctoral researcher and co-first author of the recent publication. “When applied to humans, it could help elucidate why some embryos prosper while others do not, and how to optimize conditions for conception—whether natural or assisted.”

While iG4-blastoids currently cannot advance significantly beyond the implantation phase, the researchers stress that their high fidelity to natural embryos makes them an unparalleled model system. Ongoing efforts aim to further refine the models and explore their application to human fertility research within a safe, ethical, and regulated context.

The publication is titled “Efficient stem cell-derived mouse embryo models for environmental studies.” Former Caltech graduate student Victoria Jorgensen (PhD ’23), former Caltech postdoctoral scholar Min Bao (now at First Affiliated Hospital of Wenzhou Medical University in Wenzhou, China), and Junyent are co-first authors. Along with Zernicka-Goetz, additional Caltech co-authors include former SURF student Christoph M. Häfelfinger; postdoctoral scholars Laura Amaya, Zhaodi Liao, and Dong-Yuan Chen; Brian A. Williams, director of the Transcriptome Function and Technology Program; graduate student Amanda Wu; and Matt Thomson, professor of computational biology and Heritage Medical Research Institute Investigator. Funding was provided by the National Institutes of Health, Open Philanthropy Award, the Human Frontiers Science Program, the National Natural Science Foundation of China, the Ministry of Science and Technology of China, the Swiss Study Foundation, the Werenfels Fund of the Free Academic Society Basel, and the Claudine and Hans-Heiner Zaeslin-Bustany Foundation. Zernicka-Goetz and Thomson are affiliated faculty members with the Tianqiao and Chrissy Chen Institute for Neuroscience at Caltech.

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