Models of collective migration that integrate single-cell polarity and mechanics

整合单细胞极性和力学的集体迁移模型

• 批准号: 10674021
• 负责人: Brian A Camley
• 金额: $ 39.33万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-15 至 2026-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10674021
• 关键词: 3-Dimensional; Address; Area; Biochemical; Biological; Biological Assay; Cadherins; Cell Communication; Cell Polarity; Cells; Computer Models; Contact Inhibition; Data; Development; Disease; Embryo; Epithelium; Event; Extracellular Matrix; Feedback; Fiber; Future; Geometry; Goals; Individual; Intercellular Junctions; Invaded; Link; Locomotion; Mechanics; Microfluidics; Modeling; Molecular; Morphogenesis; Motion; Motor; Myosin ATPase; Pathologic Processes; Property; Proteins; Reaction; Rupture; Stereotyping; Stream; Study models; Testing; Tissues; Touch sensation; Work; cell motility; cell type; experimental study; gastrulation; healing; in vivo; intercellular communication; mechanotransduction; migration; model building; physical model; rho GTP-Binding Proteins; tool; two-dimensional; wound; wound healing

Project Summary/Abstract Collective cell migration is critical in wound healing, morphogenesis, gastrulation, as well as in pathological processes. This collective motion arises from coordination of the biochemical polarization of individual cells. Some of the biological details of this coordination have been identified – many different cell types integrate information from cell-cell contact through cadherins in order to repolarize Rho GTPase activity. These biochemical events drive stereotyped reactions like contact inhibition of locomotion (CIL), where cells repolarize and crawl away from contact. There is a critical gap in our understanding between identifying molecular players in cell- cell interactions and being able to predict how changes in cell-cell interactions drive collective migration of an epithelial layer or an invading stream of cells. A long-term goal of the Camley group is developing computational physical models of collective cell migration to bridge this gap. This project addresses that goal by building models of collective cell migration with realistic geometry, mechanics and cell-cell signaling to study: 1. Determining the effect of cell geometry on cell-cell interactions like contact inhibition of locomotion Assays to test cell-cell interactions in collisions of migrating cells are performed on two-dimensional substrates, allowing collisions to occur between cells with broad lamellipodia. However, in vivo, cell-cell interactions occur in a context established by three-dimensional extracellular matrix, mechanical confinement, and neighboring cells, which are all known to alter motility. How can cells reliably integrate cell-cell contacts with highly variable contact areas and durations to coordinate their motion? We will develop models to describe the effect of cell and matrix geometry on cell-cell collisions. This will include recent experiments on cell-cell collisions on suspended fibers, in which our collaborators found traditional contact inhibition of locomotion is near-absent. 2. Understanding how myosin activity fluctuations and mechanotransduction regulate cell-cell rupture events Invasion of cells in both normal and diseased tissue can occur by cells breaking off from a larger group. This is a key part of collective invasion. What controls the critical step of cell-cell rupture? We hypothesize that these rare events are dependent on fluctuations in the level of motor proteins like myosin at cell-cell junctions. We will develop models to describe this strand invasion, how dissemination depends on cell motility, and the ability of cells to sense the forces exerted on junctions. We will develop tools to infer models of feedbacks between the tension at the cell-cell junction and cell motility directly from experimental data. These will be used on data from collaborators studying invasion in controlled microfluidic geometries. In addition, we will develop models studying how the size of clusters breaking from a strand depend on the strand geometry. Together, these models provide links from physical and molecular aspects of cell-cell collisions to large-scale collective migration, and will drive future questions in collective migration and development.

项目总结/摘要 集体细胞迁移在伤口愈合、形态发生、原肠胚形成以及病理学过程中是至关重要的。 流程.这种集体运动源于个体细胞的生化极化的协调。 艾德已经确定了这种协调的一些生物学细节--许多不同的细胞类型整合在一起， 通过钙粘蛋白从细胞-细胞接触中获得信息，以恢复Rho GT3活性。这些生化 事件驱动刻板的反应，如运动的接触抑制（CIL），其中细胞恢复和爬行 远离接触。在我们的理解中，识别细胞中的分子参与者之间存在着一个关键的差距- 细胞相互作用，并能够预测细胞间相互作用的变化如何驱动细胞的集体迁移， 上皮层或侵入的细胞流。Camley小组的一个长期目标是开发计算 集体细胞迁移的物理模型来弥合这一差距。该项目通过构建模型来实现这一目标 集体细胞迁移与现实的几何形状，力学和细胞间的信号传导研究： 1.确定细胞几何形状对细胞间相互作用（如运动的接触抑制）的影响 在二维基底上进行测试迁移细胞碰撞中的细胞-细胞相互作用的测定， 使得具有宽板状伪足的细胞之间发生碰撞。然而，在体内，细胞-细胞相互作用发生在 由三维细胞外基质、机械约束和邻近细胞建立的环境， 这些都能改变运动性细胞如何可靠地整合细胞与细胞之间的接触， 接触面积和持续时间来协调它们的运动？我们将开发模型来描述 细胞和基质几何结构对细胞-细胞碰撞的影响。这将包括最近关于细胞间碰撞的实验， 悬浮纤维，我们的合作者发现传统的接触抑制运动几乎不存在。 2.了解肌球蛋白活性波动和机械转导如何调节细胞-细胞破裂事件 正常组织和病变组织中的细胞入侵可以通过细胞从较大的群体中脱落而发生。这是一 集体入侵的关键部分。是什么控制着细胞间破裂的关键步骤？我们假设这些 罕见事件依赖于细胞-细胞连接处的运动蛋白如肌球蛋白水平的波动。我们将 开发模型来描述这种链入侵，传播如何取决于细胞运动，以及 细胞来感知施加在连接处的力。我们将开发工具来推断模型之间的反馈 细胞-细胞连接处的张力和细胞运动性直接来自实验数据。这些数据将用于 在受控的微生物学几何学中研究入侵的合作者。此外，我们将开发模型， 从链断裂的簇的大小如何取决于链的几何形状。 总之，这些模型提供了从细胞-细胞碰撞的物理和分子方面到大规模 集体移徙，并将推动集体移徙和发展中的未来问题。

项目成果

Cytokinesis machinery promotes cell dissociation from collectively migrating strands in confinement.

• DOI: 10.1126/sciadv.abq6480
• 发表时间: 2023-01-13
• 期刊: SCIENCE ADVANCES
• 影响因子: 13.6
• 作者: Law, Robert A.;Kiepas, Alexander;Desta, Habben E.;Ipina, Emiliano Perez;Parlani, Maria;Lee, Se Jong;Yankaskas, Christopher L.;Zhao, Runchen;Mistriotis, Panagiotis;Wang, Nianchao;Gu, Zhizhan;Kalab, Petr;Friedl, Peter;Camley, Brian A.;Konstantopoulos, Konstantinos
• 通讯作者: Konstantopoulos, Konstantinos

Picking winners in cell-cell collisions: Wetting, speed, and contact

• DOI: 10.1103/physreve.106.054413
• 发表时间: 2022-11-30
• 期刊: PHYSICAL REVIEW E
• 影响因子: 2.4
• 作者: Zadeh，Pedrom;Camley，Brian A.
• 通讯作者: Camley，Brian A.

Migration and division in cell monolayers on substrates with topological defects.

• DOI: 10.1073/pnas.2301197120
• 发表时间: 2023-07-25
• 期刊: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
• 影响因子: 11.1
• 作者: Kaiyrbekov, Kurmanbek;Endresen, Kirsten;Sullivan, Kyle;Zheng, Zhaofei;Chen, Yun;Serra, Francesca;Camley, Brian A.
• 通讯作者: Camley, Brian A.