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）有可能通过促进受损组织的再生或替换来彻底改变医学。在医学中使用hSC的关键是控制细胞间的通讯，因为这些途径是负责制造模式和整合细胞与其环境的命运的途径。在该项目中，PI将开发空间模式如何在干细胞群体中产生和演变的定量模型。这些模型的预测将通过实验进行检验。对干细胞形成的空间模式的理解将用于理解细胞间的通讯以及细胞如何与它们的环境相互作用，这在生物学、医学和生物工程中是非常重要的。最近，开发了一种用于在微图案化表面上分化hSC的测定法，该测定法产生外胚层、中胚层、内胚层等组织的前体，这些组织在空间排列中重现胚胎。该测定允许干细胞集落的容易的时间推移成像，同时细胞相互发送信号，移动并获得不同的基因表达模式。细胞可以被设计成按需产生特定的信号，然后与幼稚细胞混合，随着时间的推移，出现模式。相关信号通常以太低的水平存在而不能直接观察到，因此需要复杂的建模过程来从接收细胞的响应中推断它们。在这一领域，任何建模成功的关键是对胚胎模式的数百个基因的活动的简洁表示。现代数学为这种模型提供了模板，一个单独的项目将测试它们在线虫C.elegans器官发育中的应用。通过合作，该项目获得了许多在介导细胞信号传导的基因上带有荧光标签的hSC细胞系，物理学家们学习如何自己获得这些细胞系。内部开发的图像处理系统与实验相结合，以询问定量和预测模型是否仅用几个变量制定，并由几何形状指导。其目标是一种算法，可以在信号分子的无限组合、其浓度以及其应用的时间和持续时间中进行选择，从而最有效地从多能细胞中获得任何所需的细胞或组织。