Collaborative Research: Decoding the Self-Organization Mechanism during Myxococcus Xanthus Multicellular Development with Quantitative Experiments and Mathematical Modeling

发育生物学的一个长期难题是多细胞生物如何从一个单一的胚胎细胞发育成具有多种功能的组织和器官的有组织的三维动物。自组织过程依赖于有序的细胞生长、定向运动和细胞间的物理和化学相互作用。虽然是一个更简单的系统，但当黄粘球菌细胞组织成多细胞子实体并分化成孢子时，也会发生相同的过程。这种集体行为的潜在动力将通过遗传和生化实验、细胞跟踪研究和计算机模拟来揭示。这种跨学科的方法对于回答复杂的生物学问题至关重要，并将培养新一代跨学科的生命科学家，为21世纪生物学的挑战做好准备。此外，通过对特定模型系统的关注，该项目有望阐明具有广泛实际意义的细胞合作和自组织的一般原则。当面临营养胁迫时，黄粘球菌细胞形成的生物膜参与集体发育程序，形成多细胞子实体，其中一些细胞分化成孢子。尽管在了解这些细胞如何移动、相互传递信号和分化方面取得了巨大进展，但关于聚集成子实体的机制仍然缺乏。最近的结果对所有现存的现象模型提出了质疑。本提案的目标是开发一种协同实验和建模方法来探索聚合的各种机制。将对野生型细胞和各种发育突变体或杂交群落进行定量细胞跟踪和统计图像分析，以确定细胞如何聚集成聚集体以及细胞行为如何在分散的聚集体中发生变化。这些数据将用于形成关于聚合机制的假设，这些假设将在基于计算的代理模型的帮助下进行测试。基因缺失导致聚集缺陷的突变菌株以及不同菌株的混合物将用于改进模型。对于每个实验和模拟，模型将迭代地与关于聚合机制的逆向工程假设对齐。为了比较不同应变产生的聚集模式，并量化模拟与实验观察的一致性，将定义一组综合表征聚集模式的参数（特征）。这些参数将允许使用分层聚类将发育突变分类为影响细胞聚集的机制途径。

One of the long-standing puzzles of developmental biology is how multicellular organisms develop from a single, embryonic cell into an organized 3-dimensional animal with tissues and organs of diverse function. Self-organization processes rely on ordered cell growth, directed motility, and physical and chemical interactions between cells. Albeit a simpler system, these same processes occur when Myxococcus xanthus cells organize into a multicellular fruiting body and differentiate into spores. The underlying dynamics of this collective behavior will be uncovered using genetic and biochemical experiments, cell tracking studies, and computer simulations. Such a multidisciplinary approach is crucial to answering complex biological questions and will train a new generation of interdisciplinary life scientists ready for the challenges of 21st century biology. Moreover, with a focus on a specific model system, this project is expected to elucidate general principles of cellular cooperation and self-organization that have broad practical implications. When faced with nutritional stress, biofilms formed by Myxococcus xanthus cells engage in a collective developmental program to form multicellular fruiting bodies in which some cells differentiate into spores. Despite tremendous progress in understanding how these cells move, signal one-another and differentiate, a mechanistic picture of how aggregation into fruiting bodies occurs is still lacking. Recent results call into question all existing models of the phenomena. The goal of this proposal is to develop a synergistic experimental and modeling approach to explore various mechanisms for aggregation. Quantitative cell-tracking and statistical image analyses will be performed with wild type cells and various developmental mutants or hybrid communities to determine how cells assemble into aggregates and how cell behavior changes in aggregates that disperse. This data will be used to formulate hypotheses about the mechanism of aggregation that would be tested with the help of a computational, agent-based model. Mutant strains in which gene deletions result in aggregation defects as well as mixtures of different strains will be used to refine the model. With each experiment and simulation, the models will be iteratively aligned to reverse-engineer hypotheses about the aggregation mechanism. To compare the aggregation patterns generated by different strains and to quantify the agreement of the simulations with experimental observations, a set of parameters (features) that comprehensively characterize the aggregation patterns will be defined. These parameters will allow use of hierarchical clustering to classify developmental mutants into mechanistic pathways that affect cellular aggregation.