O'Brien Liam D, Dawes Adriana T
Department of Mathematics, The Ohio State University, 231 W 18th Ave, Columbus, 43210, Ohio, USA.
Department of Molecular Genetics, The Ohio State University, 484 W 12th Ave, Columbus, 43201, Ohio, USA.
Res Sq. 2025 Feb 26:rs.3.rs-6098751. doi: 10.21203/rs.3.rs-6098751/v1.
During development, precise cellular patterning is essential for the formation of functional tissues and organs. These patterns arise from conserved signaling networks that regulate communication both within and between cells. Here, we develop and present a model-independent ordinary differential equation (ODE) framework for analyzing pattern formation in a homogeneous cell array. In contrast to traditional approaches that focus on specific equations, our method relies solely on general assumptions about global intercellular communication (between cells) and qualitative properties of local intracellular biochemical signaling (within cells). Prior work has shown that global intercellular communication networks alone determine the possible emergent patterns in a generic system. We build on these results by demonstrating that additional constraints on the local intracellular signaling network lead to a single stable pattern which depends on the qualitative features of the network. Our framework enables the prediction of cell fate patterns with minimal modeling assumptions, and provides a powerful tool for inferring unknown interactions within signaling networks by analyzing tissue-level patterns.
在发育过程中,精确的细胞模式形成对于功能性组织和器官的形成至关重要。这些模式源于保守的信号网络,该网络调节细胞内和细胞间的通讯。在这里,我们开发并提出了一个与模型无关的常微分方程(ODE)框架,用于分析均匀细胞阵列中的模式形成。与专注于特定方程的传统方法不同,我们的方法仅依赖于关于全局细胞间通讯(细胞之间)和局部细胞内生化信号传导(细胞内)的定性特性的一般假设。先前的研究表明,仅全局细胞间通讯网络就决定了通用系统中可能出现的模式。我们基于这些结果进行论证,即对局部细胞内信号网络的额外约束会导致一种单一的稳定模式,该模式取决于网络的定性特征。我们的框架能够以最少的建模假设预测细胞命运模式,并通过分析组织水平的模式为推断信号网络内未知的相互作用提供了一个强大的工具。