Symmetry breaking and axial patterning in aggregates of mouse Embryonic Stem cells

小鼠胚胎干细胞聚集体的对称性破缺和轴向模式

• 批准号: BB/P003184/1
• 负责人: Alfonso Martinez Arias
• 金额: $ 86.26万
• 依托单位: University of Cambridge
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2016
• 资助国家: 英国
• 起止时间: 2016 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FP003184%2F1
• 关键词: Symmetry; breaking; axial; patterning; aggregates

Organisms develop from a single fertilized egg by increasing the number of cells through cell division, making those cells different from each other and, most importantly, organizing them in space to give rise to tissues and organs. This organization requires the emergence of systems of spatial coordinates that guide the arrangement of the different cells. A well accepted view of the process contends that there are gradients of special proteins, called morphogens, that can instruct cells what to do in a concentration dependent manner. This means that in a developing group of cells, there is always some pattern of instructions that cells read and that acts as a template for the process. An alternative view is that there is no such template and cells self organize from an initial situation in which all cells are equivalent. Understanding this second possibility has been difficult for lack of an adequate experimental system. Recently we have used mouse Embryonic Stem cells to create a system that recapitulates the events that take place in the early mouse embryo. This system is robust and reproducible and, together with classical genetic analysis, provides a versatile experimental tool to study processes of pattern formation. Here we propose to use this system to explore the mechanisms that pattern the early mouse embryo. Specifically we focus on a protein called Nodal that genetic analysis has shown to be crucial for the early patterning of the mouse embryo.One of the challenges of modern biology is to integrate large amounts of data, particularly from gene expression, into coherent frameworks that account for specific processes e.g the development of an organ like the heart, or a tissue, like the skin. In this process the acquisition of quantitative data about the system and its integration into predictive models is a most important part of the research. In this project we propose to do exactly this by focusing on Nodal and following preliminary results that suggest that it acts as the key element in the process of pattern formation in the aggregates as it does in the embryo, though we do not understand the mechanism of the process that mediates the patterning. In the proposed experiments we shall engineer versions of Nodal and associated proteins that will allow us to follow the patterning process live, extract quantitative data about it and combine it with classical genetic analysis in a useful and fruitful manner. The experimental system will be our patterned aggregates that will allow us to bypass the embryo and explore the role that mechanical forces play in the pattern forming process and how it interferes with the better understood biochemical events.

生物体从一个受精卵发育而来，通过细胞分裂增加细胞的数量，使这些细胞彼此不同，最重要的是，在空间中将它们组织起来，形成组织和器官。这种组织需要出现指导不同单元格排列的空间坐标系。对这一过程的一种广为接受的观点认为，存在被称为形态生成素的特殊蛋白质的梯度，它们可以指示细胞以浓度依赖的方式做什么。这意味着，在一组发育中的细胞中，总有一些指令模式可供细胞读取，并充当该过程的模板。另一种观点是，不存在这样的模板，并且单元从所有单元都相等的初始情况自组织。由于缺乏足够的实验系统，理解第二种可能性一直很困难。最近，我们使用小鼠胚胎干细胞创建了一个系统，该系统概括了小鼠早期胚胎中发生的事件。这个系统是健壮的和可重复性的，与经典的遗传分析一起，为研究模式形成过程提供了一个通用的实验工具。在这里，我们建议使用这个系统来探索小鼠早期胚胎的模式形成机制。我们特别关注一种名为Nodal的蛋白质，遗传分析表明，这种蛋白质对小鼠胚胎的早期模式至关重要。现代生物学的挑战之一是将大量数据，特别是来自基因表达的数据，整合到连贯的框架中，以解释特定过程，例如心脏等器官的发育，或皮肤等组织的发育。在这一过程中，获取有关系统的定量数据并将其集成到预测模型中是研究的最重要部分。在这个项目中，我们建议通过关注Nodal并遵循初步结果来实现这一点，这些初步结果表明，Nodal在聚集体中的图案形成过程中扮演着关键元素的角色，就像它在胚胎中所做的那样，尽管我们并不了解介导图案形成的过程的机制。在拟议的实验中，我们将设计不同版本的Nodal和相关蛋白质，使我们能够实时跟踪构图过程，提取有关它的定量数据，并以有用和富有成效的方式将其与经典遗传分析相结合。实验系统将是我们的图案聚集体，它将允许我们绕过胚胎，探索机械力在图案形成过程中所起的作用，以及它如何干扰更好地理解的生化事件。

项目成果

Fractional viscoelastic models for power-law materials

幂律材料的分数阶粘弹性模型

• DOI: 10.48550/arxiv.2003.07834
• 发表时间: 2020
• 作者: Bonfanti A

Emergence of a node-like population within an in vitro derived Neural Mesodermal Progenitors (NMPs) population

• DOI: 10.1101/326371
• 发表时间: 2018-05
• 期刊: bioRxiv
• 作者: Shlomit Edri;P. Hayward;W. Jawaid;A. M. Arias