Geometry, Genetics and Development

几何、遗传学和发育

• 批准号: 1502151
• 负责人: Eric Siggia
• 金额: $ 45.69万
• 依托单位: Rockefeller University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-01 至 2020-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1502151&HistoricalAwards=false
• 关键词: Geometry; Genetics; Development

Stem cells (SC) have the potential to revolutionize medicine by facilitating the regeneration or replacement of damaged tissues. Crucial for the use of hSC in medicine is control over inter-cell communication, since those pathways are the ones responsible for making patterns and integrating the fate of a cell with its environment. In this project the PI will develop quantitative models of how spatial patterns arise and evolve in populations of stem cells. The predictions of these models will be tested experimentally. The understanding of the spatial patterns formed by stem cells will be used to understand cell-cell communication and how cells interact with their environment that is very important in biology, medicine, and bioengineering.Recently an assay was developed for differentiating hSC on micropatterned surfaces, that generates the precursors to ectoderm, mesoderm, endoderm, etc. tissues in a spatial arrangement that recapitulates the embryo. This assay permits easy time lapse imaging of stem colonies while the cells signal to each other, move, and acquire distinct patterns of gene expression. Cells can be engineered to produce specific signals on demand and then mixed with naive cells and the emergent patterns followed over time. The relevant signals are generally present at too low a level to be observed directly, so a complex modeling procedure is needed to infer them from the response of the receiving cells. Critical for the success of any modeling in this area are succinct representations for the activity of the hundreds of genes that pattern an embryo. Modern mathematics provides the template for such models, and a separate project will test their application to the development of an organ in the nematode C.elegans. Through a collaboration, this project has access to many hSC lines with fluorescent tags on the genes that mediate cell signaling, and Physicists learn how to derive such lines themselves. Image processing systems developed in house are integrated with experiments to ask whether quantitative and predictive models formulated with only a few variables and guided by geometry are feasible. The goal is an algorithm to select among the infinite combinations of signaling molecules, their concentrations, and the time and duration of their application, the most efficient way to derive any desired cell or tissue from pluripotent cells.

干细胞（SC）有可能通过促进或替换受损组织的再生或替代。对于医学中HSC的使用至关重要的是控制细胞间通信的控制，因为这些途径是负责制定模式并将细胞命运与环境相结合的途径。在该项目中，PI将开发定量模型，说明干细胞种群中如何出现空间模式和演变。这些模型的预测将进行实验测试。对干细胞形成的空间模式的理解将用于了解细胞细胞的通信以及细胞如何与其在生物学，医学和生物工程中非常重要的环境相互作用。开发了一种用于在微图表上区分HSC的测定法，从而在微图表上区分HSC，从而产生了胚胎，内胚层，内胚层，在一个杂质中产生的前体。该测定法可以轻松地对茎菌落的时间衰减成像，而细胞相互信号，移动并获得不同的基因表达模式。可以设计细胞以按需产生特定的信号，然后与幼稚的细胞混合，并且随着时间的推移随着时间的流逝而遵循的新出现模式。相关信号通常存在于A级过低以至于无法直接观察到，因此需要一个复杂的建模程序来从接收单元的响应中推断出它们。对于该领域的任何建模的成功至关重要的是对胚胎的数百个基因活性的简洁表示。现代数学为此类模型提供了模板，一个单独的项目将测试其在线虫C.Elegans中器官开发中的应用。通过协作，该项目可以在介导细胞信号的基因上访问许多HSC线，并在介导细胞信号的基因上使用荧光标签，并且物理学家学习了如何得出此类线路。内部开发的图像处理系统与实验集成在一起，以询问仅使用几个变量制定的定量和预测模型，而在几何形状的指导下是可行的。目标是一种算法，可以在信号分子的无限组合中进行选择，其浓度以及其应用的时间和持续时间，这是从多能细胞中获取任何所需的细胞或组织的最有效方法。