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纽约医学院斯图尔特·A·纽曼博士马克·阿尔伯博士，圣母大学项目摘要本项目的目标是定义和测试一种基于激活剂-抑制物的脊椎动物肢体间充质细胞骨骼模式形成机制。该策略涉及为这一过程与三个截然不同但相互关联的“模型”进行合作：(I)利用高密度(‘微质量’)禽肢间充质细胞培养的易于操作的体外实验模型；(Ii)关注经实验确认的基因表达-生长因子-细胞行为相互作用的概念性发育模型，该模型在体内和体外构图过程中常见的基因表达-生长因子-细胞行为相互作用；(Iii)基于离散细胞自动机(CA)的计算模型，该模型已被证明在半定量意义上捕捉到体外模型的主要特征，该假设源于发育模型。由计算模型指定的关键交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，在这之前，有必要确定这些相互作用是否唯一地模拟了体外软骨形成的模式，以及引入额外的、经实验证实的分子相互作用和几何因素是否增加或降低了模型对体外结果的保真度。计算模型是“面向主体的”模型，它用晶格上的点来表示细胞，这些点遵守实验发现所驱动的规则。“细胞”作为自主主体遵循这些规则，与其他细胞以及细胞活动产生的微环境相互作用。这些规则包括细胞的随机运动，与纤维连接蛋白相对应的底物黏附分子的产生和侧向沉积，与刺激SAM产生的转化生长因子-β相对应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(“抑制物”)。细胞自动机被模拟在二维正方形格子上模拟准2D微团培养。Newman实验室将在体外错误表达和抑制侧抑制激发子和候选抑制分子转化生长因子-β、纤维连接蛋白、FGF2和8的表达，并将模式结果与CA模型的相应操作进行比较；Alber博士和他的同事们将改进CA模型，以提供更逼真的形状，允许细胞在第三维度移动和积累，使它们表现出不同的粘附性，并将开发一套适用于微质量培养和模拟的模式分析方法，以便于在体外和计算机结果之间进行详细比较。广泛的影响：该项目有望产生超出所解决的特定科学问题的几个好处。细胞自动机方法是一种通用的工具，可以为从事模式形成领域工作的发展生物学家提供一种设计实验、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以及数学、物理和计算科学家的合作努力提供一个原型。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的研究经验，他们都将花费时间在交替领域的研究小组中。

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.