Testing a Developmental Mechanism by an Integrated Empirical-Computational Approach

通过综合经验计算方法测试发育机制

• 批准号: 0344647
• 负责人: Stuart Newman
• 金额: $ 48万
• 依托单位: New York Medical College
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-04-15 至 2008-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0344647&HistoricalAwards=false
• 关键词: Testing; Developmental; Mechanism; Integrated; Empirical

Testing a Developmental Mechanism by an Integrated Empirical-Computational ApproachStuart A. Newman, Ph.D., New York Medical CollegeMark Alber, Ph.D., University of Notre DamePROJECT SUMMARYThe objective of this project is to define and test an activator-inhibitor based mechanism for skeletal pattern formation in vertebrate limb mesenchymal cells. The strategy involves working with three distinct but interrelated "models" for this process: (i) a readily manipulable in vitro experimental model utilizing high-density ('micromass") cultures of avian limb mesenchymal cells; (ii) a conceptual developmental model that focuses on experimentally confirmed gene expression-growth factor-cell behavioral interactions common to the in vivo and in vitro patterning process; and (iii) a discrete cellular automaton (CA)-based computational model that has been shown to capture, in a semi-quantitative sense, the major features of the in vitro model, under assumptions that derive from the developmental model. The key interactions specified by thecomputational model ultimately can be integrated into a multiscale, continuous representation of limb development in vivo. Before this is possible, however, it is necessary to determine whether these interactions uniquely simulate chondrogenic pattern formation in vitro, and whether introduction of additional, experimentally-confirmed molecular interactions and geometrical considerations increases or decreases the fidelity of the model to the in vitro results.The computational model is an "agent-oriented" model that represents cells by points on a lattice which obey rules motivated by experimental findings. The "cells" follow these rules as autonomous agents, interacting with other cells and with microenvironments produced by cell activities. The rules include random cell motion, production and lateral deposition of a substrate adhesion molecule corresponding to fibronectin, production and release of a diffusible activator, corresponding to TGF-B that stimulates production of the SAM, and another diffusible factor ("inhibitor") that suppresses the activity of the activator. The cellular automaton is modeled on a 2- dimensional square lattice to emulate the quasi-2D micromass culture.The Newman laboratory will misexpress and inhibit expression of TGF-B , fibronectin, FGF2 and 8 (elicitors of lateral inhibition) and candidate inhibitory molecules in vitro and compare pattern results with corresponding manipulations of the CA model; Dr. Alber and his associates will refine the CA model so as to provide cells with more realistic shapes, allow them to move and accumulate in a third dimension, cause them to exhibit differential adhesion, and will develop a set of quantitative methods for pattern analysis, applicable to both micromass cultures and simulations, so as to facilitate detailed comparison between in vitro and in silico results.Broader impact: The project can be expected to yield several benefits that extend beyond the particular scientific problem addressed. The cellular automata approach is a general tool that can provide developmental biologists working in the area of pattern formation with a way of designing experiments, making predictions, and testing hypotheses. The cross-disciplinary nature of the project will provide a prototype for collaborative efforts by experimental biologists and mathematical, physical, and computational scientists. The work will also have educational value by providing interdisciplinary research experience to graduate students in experimental biology and applied mathematics, who will all spend time in the research groups of the alternate field.

通过综合经验计算方法测试发育机制Stuart A. Newman 博士，纽约医学院Mark Alber 博士，圣母大学项目摘要该项目的目标是定义和测试基于激活剂-抑制剂的机制，用于脊椎动物肢体间充质细胞中的骨骼模式形成。该策略涉及针对此过程使用三个不同但相互关联的“模型”：（i）利用禽肢间充质细胞的高密度（“微团”）培养物的易于操作的体外实验模型；（ii）概念性发育模型，重点关注通过实验证实的体内和体外模式形成过程中常见的基因表达-生长因子-细胞行为相互作用；以及（iii）离散细胞 基于自动机 (CA) 的计算模型已被证明可以在半定量意义上捕获体外模型的主要特征，并在源自发育模型的假设下进行。计算模型指定的关键相互作用最终可以集成到体内肢体发育的多尺度、连续表示中。然而，在此之前，有必要确定这些相互作用是否唯一地模拟软骨形成模式 体外形成，以及引入额外的、经实验证实的分子相互作用和几何考虑因素是否会增加或降低模型对体外结果的保真度。计算模型是一种“面向代理”的模型，通过网格上的点表示细胞，这些点遵守由实验结果驱动的规则。 “细胞”作为自主代理遵循这些规则，与其他细胞和产生的微环境相互作用 通过细胞活动。这些规则包括随机细胞运动、对应于纤连蛋白的底物粘附分子的产生和横向沉积、对应于刺激 SAM 产生的 TGF-B 的扩散激活剂的产生和释放，以及抑制激活剂活性的另一种扩散因子（“抑制剂”）。元胞自动机以二维方格为模型来模拟 准二维微团培养。纽曼实验室将在体外错误表达和抑制 TGF-B、纤连蛋白、FGF2 和 8（侧抑制诱导子）和候选抑制分子的表达，并将模式结果与 CA 模型的相应操作进行比较； Alber博士和他的同事将完善CA模型，为细胞提供更真实的形状，让它们移动和积累 在第三个维度上，使它们表现出不同的粘附力，并将开发一套适用于微团培养和模拟的模式分析定量方法，以便于体外和计算机结果之间的详细比较。更广泛的影响：预计该项目将产生超出所解决的特定科学问题的多种好处。细胞自动机方法是一种通用工具，可以为从事模式形成领域工作的发育生物学家提供帮助 通过设计实验、做出预测和检验假设的方法。该项目的跨学科性质将为实验生物学家和数学、物理和计算科学家的合作提供原型。这项工作还将具有教育价值，为实验生物学和应用数学的研究生提供跨学科研究经验，他们都将在替代领域的研究小组中度过时光。