Request for Administrative Supplement for R01GM097576, Systematic Multi-scale Analysis of Tissue Morphogenesis

组织形态发生的系统多尺度分析 活体成像的最新进展提供了前所未有的机会来研究细胞行为和细胞如何- 细胞间的相互作用在体内形成了复杂的组织。我们建议开发新的计算方法 分析和合成来自实时成像的复杂表型数据，并将其应用于研究如何 集体细胞行为在组织形态发生中调节细胞运动，并实现稳健的细胞定位。 我们使用线虫胚胎发生作为我们的模型，在那里我们开发了高通量的技术 成像和自动细胞跟踪，允许我们扰乱数百个基因并进行详细的谱系 对数以千计的胚胎进行分析。我们提出了三个目标。首先，我们将开发新的算法来精确地 在致密组织中的细胞跟踪，包括一种基于细胞核多色标记的新方法。单元格精度 追踪是系统分析个体细胞行为的主要瓶颈，尤其是在致密组织中。 这一努力将提供具有更高准确性的新工具，这反过来又使得对 大型图像数据集中的单个细胞行为。第二，我们将研究调节细胞的新机制 在组织形态发生中的运动，并实现稳健的细胞定位。其中包括一种新形式的 多细胞花环，其中连续的边缘收缩和分辨率事件调节定向细胞 有动静。我们还提出了一种新的稳健的细胞定位模型，在该模型中细胞评估其邻域 并在缺少所需邻居时激活移动。我们将阐明潜在的分子和 结合遗传扰动、系统单细胞分析和一种新方法的细胞机制 对单个细胞进行实时跟踪和光学操作。这项研究将拓宽我们对 在细胞和组织水平上的发育噪声控制。第三，我们将开发一种新的基于代理的 集成复杂表型数据的建模框架，用于复杂组织的多尺度分析。我们会 开发一个除线虫以外的通用软件包。然后我们将应用它来检查血统 基于上千个扰动的线虫胚胎发生中的分化和组织形态发生 在这项研究和我们之前的研究中收集的胚胎。特别是，我们将进一步检查单元中健壮性 通过将上述模型与基于WNT的主轴控制的类似PCP模型进行集成来定位。这项工作将 提供了一种强大的工具来检查跨分子、细胞和组织水平的复杂组织，并进一步 对组织形态发生的稳健性的见解。

Systematic Multi-scale Analysis of Tissue Morphogenesis Recent progress in live imaging offers unprecedented opportunities to examine cellular behaviors and how cell- cell interactions give rise to complex tissues in vivo. We propose to develop novel computational approaches to analyze and synthesize the complex phenotypic data from live imaging and apply them to study how collective cell behaviors mediate cell movement in tissue morphogenesis and achieve robust cell positioning. We use C. elegans embryogenesis as our model, where we have developed techniques for high throughput imaging and automated cell tracking that allow us to perturb hundreds of genes and conduct detailed lineage analysis in thousands of embryos. We propose three aims. First, we will develop new algorithms for accurate cell tracking in dense tissues, including a new method based on multi-color labeling of nuclei. Accuracy in cell tracking is a major bottleneck in systematic analysis of individual cell behaviors, especially in dense tissues. This effort will provide novel tools with improved accuracy, which in turn allows more effective analysis of individual cell behaviors in large image datasets. Second, We will examine novel mechanisms that mediate cell movement in tissue morphogenesis and achieve robust cell positioning. These include a novel form of multicellular rosette where sequential edge contraction and resolution events mediate directional cell movement. We also propose a novel model of robust cell positioning where cells assess their neighborhoods and activate movement when a desired neighbor is missing. We will elucidate the underlying molecular and cellular mechanisms combining genetic perturbations, systematic single-cell analysis and a novel method for real-time tracking and optical manipulation of single cells. This study will broaden our understanding of developmental noise control at the cellular and tissue levels. Third, We will develop a novel agent-based modeling framework to integrate complex phenotypic data for multi-scale analysis of complex tissues. We will develop a software package for general use beyond C. elegans. We will then apply it to examine lineage differentiation and tissue morphogenesis in C. elegans embryogenesis based on the thousands of perturbed embryos collected in this and our previous studies. In particular, we will further examine robustness in cell positioning by integrating the model above with a PCP-like model of Wnt-based spindle control. This work will provide a powerful tool to examine complex tissues across molecular, cellular and tissue levels, and further insights on the robustness of tissue morphogenesis.