Geometry, Genetics and Development

干细胞(SC)通过促进受损组织的再生或替换，有可能给医学带来革命性的变化。在医学上使用HSC的关键是控制细胞间的通讯，因为这些通路负责形成模式并将细胞的命运与其环境结合起来。在这个项目中，PI将开发干细胞群体中空间模式如何产生和演变的量化模型。这些模型的预测将在实验中得到验证。对干细胞形成的空间模式的理解将被用来理解细胞与细胞之间的交流以及细胞如何与环境相互作用，这在生物学、医学和生物工程中非常重要。最近，一种在微图案表面区分干细胞的方法被开发出来，它以一种重塑胚胎的空间排列方式产生外胚层、中胚层、内胚层等组织的前体。这种分析方法可以轻松地对干细胞克隆进行延时成像，同时细胞之间相互传递信号，移动并获得不同的基因表达模式。细胞可以根据需要产生特定的信号，然后与幼稚的细胞混合，随着时间的推移，出现的模式也会随之出现。相关信号通常存在于太低的水平而不能直接观察到，因此需要复杂的建模过程来从接收小区的响应中推断它们。对这一领域的任何建模的成功至关重要的是，对形成胚胎图案的数百个基因的活动的简明表示。现代数学为这种模型提供了模板，另一个单独的项目将测试它们在线虫器官发育中的应用。通过合作，该项目获得了许多在介导细胞信号的基因上带有荧光标签的HSC株系，物理学家们学习如何自己推导出这样的株系。室内开发的图像处理系统与实验相结合，以询问仅用几个变量建立的、由几何指导的定量和预测模型是否可行。我们的目标是一种算法，从无限的信号分子组合、它们的浓度、它们的应用时间和持续时间中进行选择，这是从多能细胞中获得任何所需细胞或组织的最有效方式。

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.