Collective Gradient Sensing and Cell-to-Cell Variability - Theory and Experiment

这个项目将有助于理解细胞如何协同工作来解释外部信号并共同做出决定。埃瓦尔德研究小组的早期工作表明，组织中的细胞相互协作，做出决定，比如选择何时何地移动。这种合作可以帮助做出更可靠的决策。这方面的一个例子是，当多个细胞共同工作以跟踪化学信号时，它们比单个细胞本身更精确和可靠。这个项目研究了这是如何发生的，以及当每个细胞对信号的反应高度不同时--当细胞单独不可靠时--细胞如何协同工作。这个项目有两种关键类型的实验--这两种实验都有计算模型和数学理论作为补充。在第一种实验类型中，将创建一个高度可变的细胞集合，这些细胞组合在一起，它们认为它们看到了告诉它们移动或生长的信号(活动细胞)，而那些没有看到信号的细胞(非活动细胞)。为了了解这些细胞如何共同做出决定，将使用数学模型来预测细胞根据活跃细胞的初始位置做出的最终决定-组织生长的方向。在第二种实验类型中，细胞将暴露在外部信号中。分支机构将在多大程度上遵循这一信号？这是否受细胞变异(活跃细胞的不同部分)的影响？这些实验结果和其他结果将用计算模型来描述，该模型既包括细胞之间的物理力，也包括细胞感知的分子的运动。了解细胞如何以这种方式合作将有助于我们理解发育中的胚胎是如何可靠形成的--当细胞最终出现在错误的位置时，这可能会导致出生缺陷。该项目还将支持从高中生到研究生的培训。高中生将通过女性科学与工程(WISE)计划从巴尔的摩的学校招募来参与研究。此外，通过该项目培训的学生将接受协作写作和外联方面的培训。组织和器官内的细胞为了移动和感知信号而相互协作；这种协作使它们能够完成单个细胞无法完成的任务。一个戏剧性的例子，也是这个项目的主要焦点，是集体梯度感应，即一组细胞测量信号梯度，即使单个细胞无法测量。集体梯度感应涉及细胞之间的比较，并将受到细胞间可变性的强烈影响，因为即使是遗传上相同的细胞也可能具有高度不同的运动性和对信号的反应。理解集体梯度感应将需要量化这些细胞间的差异并对其后果进行建模。该项目是一种实验和理论相结合的方法，旨在通过以下方式了解集体梯度感应和细胞间变异：1)测试乳腺器官中可诱导变异的现有假说；2)开发改进的模型，解决细胞运动、细胞周期和细胞分裂的变异问题。从理论上讲，集体梯度感应的准确性应该取决于细胞变异性和组织重新排列能力之间的平衡。变异性和流动性将在分枝乳房有机体的实验中控制和测量，这些实验经历了集体梯度传感。将对有机化合物进行实验，以同时表征传感和流动性，以检验这一想法。此外，通过研究马赛克类有机化合物，还将诱导人工变异。这些实验将用Camley小组以前开发的简单随机模型进行分析。在这些实验结果的推动下，将使用自推进粒子模型和生化/机械细胞模型来创建具有细胞间信号、机械和运动性变化的有机物的新计算模型。评估理论将被用来找出准确的群体决策的基本极限。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This project will help understand how cells can work together to interpret external signals and collectively make decisions. Earlier work from the Ewald group showed that cells in tissues cooperate to make decisions, such as choosing when and where to move. This cooperation can help make more reliable decisions. One example of this is that when many cells work together to follow a chemical signal, they are more precise and reliable than a single cell on its own. This project studies how this happens, and how cells can work together even when each cell can have highly variable responses to a signal – when cells are individually unreliable. This project has two critical types of experiments – both of which supplemented by computational modeling and mathematical theory. In the first experiment type, a highly variable collection of cells will be created, combined of cells that think they see a signal telling them to move or grow (active cells), and those that don’t (inactive cells). To understand how these cells work together to make decisions, mathematical models will be used to predict the final decision the cells make – the direction of tissue growth – from the initial location of the active cells. In the second experiment type, the cells will be exposed to an external signal. How precisely will branch locations follow this signal? Is this affected by cell variation (different fractions of active cells)? These experimental results and others will be described with computational models that include both the physical forces between cells and the motion of the molecules that the cells are sensing. Understanding how cells cooperate in this way will help us understand how developing embryos are reliably formed – when cells end up in the wrong place, this can lead to birth defects. This project will also support the training of students from the high school level to graduate students. High school students will be recruited from Baltimore schools through the Women in Science and Engineering (WISE) program to participate in research. In addition, students trained through this project will be trained in collaborative writing and outreach. Cells within tissues and organs cooperate in order to move and sense signals; this cooperation allows them to perform tasks that single cells cannot. A dramatic example, and the major focus of this project, is collective gradient sensing, where groups of cells measure a signal gradient, even when a single cell cannot. Collective gradient sensing involves comparisons between cells, and will be strongly affected by cell-to-cell variability, as even genetically identical cells can have highly variable motilities and responses to signal. Understanding collective gradient sensing will require quantifying these cell-to-cell variations and modeling their consequences. This project is a combined experiment and theory approach to understanding collective gradient sensing and cell-to-cell variation by 1) testing existing hypotheses in mammary organoids where variability can be induced, and 2) developing improved models that address variability in cell motility, cell cycle, and cell division. Collective gradient sensing accuracy should – in theory – depend on a balance of cell variability and the ability of a tissue to re-arrange. Variability and fluidity will be controlled and measured in experiments on branching mammary organoids, which undergo collective gradient sensing. Experiments on organoids will be performed to simultaneously characterize sensing and fluidity to test this idea. In addition, artificial variability will be induced by studying mosaic organoids. These experiments will be analyzed with simple stochastic models previously developed by the Camley group. Motivated by the results of these experiments, new computational models of organoids with cell-to-cell variation in signaling, mechanical, and motility properties will be created using both self-propelled particle and biochemical/mechanical cell models. Estimation theory will be used to find fundamental limits to accurate group decisions.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.