Integrating mechanical and biochemical signals in cell migration through membrane dynamics

通过膜动力学将机械和生化信号整合到细胞迁移中

• 批准号: 2282404
• 金额: --
• 依托单位: University of Manchester
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2019
• 资助国家: 英国
• 起止时间: 2019 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2282404
• 关键词: Integrating; mechanical; biochemical; signals; cell

Cells respond to a myriad of cues from their environment, including mechanical signals from the extracellular matrix and biochemical cues from growth factors and cytokines. How these different types of signal are integrated to produce the appropriate cellular response is not known. We aim to determine how migrating cells decode their environment to move efficiently in complex environments, and understand how cells are able to integrate different types of signal to generate a coordinated response. Migrating cells respond to chemical (chemotaxis), extracellular matrix ligand (haptotaxis) and physical (durotaxis) stimuli by recognising signals at the cell surface. The plasma membrane serves as the physical boundary of the cells, and many signalling processes are organised at this junction between the intra- and extra-cellular environments. Cells sense growth factors/cytokines through signalling receptors, and extracellular matrix properties through cell-matrix adhesion complexes, and hence the availability of such receptors at the membrane (regulated by vesicle trafficking) is of major importance. In addition, the plasma membrane has been shown to control cell behaviour by exerting force (tension) on the underlying cytoskeleton. We hypothesise that membrane dynamics, including vesicle trafficking and membrane tension, orchestrate signals at the plasma membrane to integrate different classes of stimuli and direct cell migration and invasion. We will use direct measurements of localised signalling, forces exerted at the cell-matrix interface and on the plasma membrane (live cell imaging, super-resolution, FRET/FLIM of biosensors) to determine how cells respond to migratory stimuli. Using proteomics, we will establish how signalling networks are reorganised to allow migrating cells to adapt to changes in the physical and biochemical environment. This information will be used to inform mathematical models, to understand how these seemingly independent signalling networks are integrated. By combining state-of-the-art imaging approaches with proteomics and computational models in an iterative process, well will build a comprehensive understanding of how signalling networks are re-wired in the face of the changing landscape faced by cells migrating within complex microenvironments.

细胞对来自其环境的无数线索做出反应，包括来自细胞外基质的机械信号和来自生长因子和细胞因子的生化线索。这些不同类型的信号如何整合以产生适当的细胞反应尚不清楚。我们的目标是确定迁移细胞如何解码它们的环境，以便在复杂的环境中有效地移动，并了解细胞如何能够整合不同类型的信号以产生协调的响应。迁移细胞通过识别细胞表面的信号对化学（趋化性）、细胞外基质配体（趋触性）和物理（硬旋转）刺激作出反应。质膜作为细胞的物理边界，许多信号传导过程都是在细胞内和细胞外环境之间的连接处组织的。细胞通过信号受体感知生长因子/细胞因子，并通过细胞-基质粘附复合物感知细胞外基质性质，因此膜上此类受体的可用性（由囊泡运输调节）非常重要。此外，质膜已被证明通过对下面的细胞骨架施加力（张力）来控制细胞行为。我们假设，膜动力学，包括囊泡运输和膜张力，编排信号在质膜整合不同类别的刺激和直接细胞迁移和入侵。我们将使用直接测量局部信号，在细胞-基质界面和质膜上施加的力（活细胞成像，超分辨率，生物传感器的FRET/FLIM）来确定细胞如何响应迁移刺激。利用蛋白质组学，我们将建立信号网络是如何重组的，以允许迁移细胞适应物理和生化环境的变化。这些信息将被用于建立数学模型，以了解这些看似独立的信号网络是如何整合的。通过在迭代过程中将最先进的成像方法与蛋白质组学和计算模型相结合，我们将全面了解信号网络如何在复杂微环境中迁移的细胞所面临的不断变化的景观中重新布线。