A computational modeling approach for predicting multicell spheroid patterns based on signaling-induced differential adhesion.
A computational modeling approach for predicting multicell spheroid patterns based on signaling-induced differential adhesion.
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DOI：
10.1371/journal.pcbi.1010701
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发表时间：
2022-11
影响因子：
4.3
通讯作者：
中科院分区：
文献类型：
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包括胚胎发生和肿瘤发生在内的生理和病理过程依赖于单个细胞集体工作形成多细胞模式的能力。在这些异质多细胞系统中，细胞-细胞信号传导诱导细胞之间的差异粘附，从而导致组织水平的模式。然而，模式形成对信号或细胞粘附过程强度变化的敏感性尚不清楚。先前的研究利用综合工程异质多细胞球体系统探索了这些问题，其中细胞亚群参与双向细胞间信号传导来调节不同钙粘蛋白的表达。虽然工程细胞系统提供了很好的实验工具来观察细胞群体中的模式形成，但这些系统的计算模型可以用来更系统地探索信号和粘附参数的特定组合如何驱动独特模式的出现。我们开发并验证了二维和三维基于agent的球体模式模型（ABMs），用于先前描述的具有调节N-和P-cadherin表达的双向信号通路的细胞。对模型预测的系统探索，其中一些已经通过实验验证，揭示了细胞播种参数、信号事件的顺序、诱导钙粘蛋白表达的概率和同型粘附强度如何影响模式的形成。无监督聚类也用于将信号和粘附参数的组合映射到由ABM预测的这些独特的球体模式。最后，我们展示了如何将该模型部署到基于期望的最终多细胞模式设计新的合成细胞信号通路。在胚胎发生过程中，细胞的自组织能力对功能组织的组装至关重要，而导致肿瘤发生和转移的分子畸变会损害细胞的自组织能力。学习细胞自组装的规则将为理解这种生理和病理生理过程提供一种新的方法，并为从零开始设计用于治疗应用的组织创建指导手册。生物学家已经开始通过逆向工程来学习自我组装的规则，也就是说，通过设计生物化学回路来控制细胞如何相互粘附。例如，这些方法可以产生简单的多细胞结构，这些结构可以自组装成一种细胞类型的核心，周围是另一种细胞类型的外壳。然而，工程更复杂的组织模式需要探索大范围的电路结构和参数。为了以有指导和系统的方式促进这一探索，我们创建了一个计算模型，该模型预测了表达粘附蛋白的不同回路的细胞混合物如何在由数百个细胞组成的球状组织中相互作用，形成不同的模式。我们的模型能够设计内部分子信号通路，允许细胞用作具有特定结构和最终功能的自组装组织的构建块。
Physiological and pathological processes including embryogenesis and tumorigenesis rely on the ability of individual cells to work collectively to form multicell patterns. In these heterogeneous multicell systems, cell-cell signaling induces differential adhesion between cells that leads to tissue-level patterning. However, the sensitivity of pattern formation to changes in the strengths of signaling or cell adhesion processes is not well understood. Prior work has explored these issues using synthetically engineered heterogeneous multicell spheroid systems, in which cell subpopulations engage in bidirectional intercellular signaling to regulate the expression of different cadherins. While engineered cell systems provide excellent experimental tools to observe pattern formation in cell populations, computational models of these systems may be leveraged to explore more systematically how specific combinations of signaling and adhesion parameters can drive the emergence of unique patterns. We developed and validated two- and three-dimensional agent-based models (ABMs) of spheroid patterning for previously described cells engineered with a bidirectional signaling circuit that regulates N- and P-cadherin expression. Systematic exploration of model predictions, some of which were experimentally validated, revealed how cell seeding parameters, the order of signaling events, probabilities of induced cadherin expression, and homotypic adhesion strengths affect pattern formation. Unsupervised clustering was also used to map combinations of signaling and adhesion parameters to these unique spheroid patterns predicted by the ABM. Finally, we demonstrated how the model may be deployed to design new synthetic cell signaling circuits based on a desired final multicell pattern. The remarkable ability of cells to self-organize is critical for the assembly of functional tissues during embryogenesis and is impaired by the molecular aberrations that lead to tumorigenesis and metastasis. Learning the rules of cellular self-assembly will provide a new way to understand such physiological and pathophysiological processes and create an instruction manual for designing tissues from scratch for therapeutic applications. Biologists have begun to learn the rules of self-assembly through reverse engineering–that is, through engineering biochemical circuits that control how cells adhere to one another. These approaches can yield simple, multi-cell structures that self-assemble into a core of one cell type surrounded by a shell of another cell type, for example. However, engineering more complex tissue patterns requires exploring a large domain of circuit structures and parameters. To facilitate this exploration in a guided and systematic manner, we created a computational model that predicts how mixtures of cells with different circuity for expressing adhesion proteins will interact to form varied patterns in spheroidal tissues comprised of hundreds of cells. Our model enables the design of internal molecular signaling circuitry that permits cells to be used as building blocks for self-assembled tissues with specific structures, and ultimately functions.
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影响因子：
2.7
作者：
BRONNERFRASER, M;WOLF, JJ;MURRAY, BA
通讯作者：
MURRAY, BA
DOI：
10.1073/pnas.1815345116
发表时间：
2019-01-02
影响因子：
11.1
作者：
Bocci, Federico;Gearhart-Serna, Larisa;Jolly, Mohit Kumar
通讯作者：
Jolly, Mohit Kumar
影响因子：
11.2
作者：
Buonato JM;Lazzara MJ
通讯作者：
Lazzara MJ
影响因子：
7.2
作者：
Batlle, Eduard;Wilkinson, David G.
通讯作者：
Wilkinson, David G.
影响因子：
5.8
作者：
Izaguirre, JA;Chaturvedi, R;Glazier, JA
通讯作者：
Glazier, JA