Supervised morphogenesis in gastruloids (SUMO)

缺乏能够真实反映体内生理过程的真实的体外器官模型是影响生物和医学科学的主要障碍。目前的黄金标准是动物实验，但越来越明显的是，这些模型大多无法概括人类生理学。此外，动物实验是有争议的，科学界的共同目标是将动物的使用减少到严格必要的最低限度。干细胞工程器官模型的出现代表了动物研究的唯一可行选择。然而，目前的有机体技术还没有生产出医学科学真正需要的更大的生理相关器官模型。具体地说，目前的器官太小，没有血管化，并且缺乏体内发现的三维组织。在这个跨学科的项目中，我们的目标是通过使用最新开发的由尖端生物工程和人工智能指导的原肠技术来挑战所有这些限制。半乳糖是通过启动非常早期的发育过程而形成的，并沿着高度协调的三轴过程发展，非常类似于哺乳动物的胚胎发生。此外，原肠类可以同时发育多个器官前体，因此与传统的单组织器官相比构成了重要的改进。为了挖掘胃肠技术的潜力，我们将首先进行大型测序和成像实验，以优化器官诱导胃肠的发育轨迹。然后，我们将把这些数据集构建成一个多模式数据矩阵，以确定心血管和前庭发育的胃液候选。具体地说，我们将确定显示出强大的血管生成的候选对象，作为以后通过与内皮细胞吻合进行血管形成的候选对象。

The lack of realistic in vitro organ models that can faithfully represent in vivo physiological processes is a major obstacle affecting the biological and medical sciences. The current gold standard is animal experiments, but it is increasingly clear that these models mostly fail to recapitulate the human physiology. Moreover, animal experiments are controversial, and it is a common goal in the scientific community to minimize the use of animals to a strictly necessary minimum. The emergence of stem cell engineered organ models called organoids represents the only viable alternative to animal research. However, current organoid technology is yet to produce the larger physiologically relevant organ models that the medical sciences really need. Specifically, current organoids are too small, not vascularized and lack the 3-dimensional organization found in vivo. In this interdisciplinary project we aim to challenge all these limitations by using the recently developed gastruloid technology guided by cutting edge bioengineering and artificial intelligence. Gastruloids are formed by initiating the very early developmental processes and develops along a highly coordinated three axial process that closely resembles mammalian embryogenesis. Moreover, gastruloids can develop several organ precursors simultaneously and thus constitutes important improvements over conventional single-tissue organoids. To harvest the potential of gastruloid technology we will first implement large sequencing and imaging experiments to optimize the developmental trajectory of gastruloids for organ inductions. We will then build these datasets into a multimodal data matrix to identify gastruloid candidates for cardiovascular and foregut development. Specifically, we will identify candidates that show strong vasculogenesis as candidates for later vascularisation by anastomose with endothelial cells.