Collaborative Research: Computational methods for understanding the influence of cellular geometry and substructure on signaling

为了能够预测和控制细胞的行为，有必要了解它们是如何检测、处理和响应外部信号的。该奖项将开发准确和高效的数值方法，用于在全细胞尺度上研究细胞如何响应和处理外部信号。这将通过开发新的基于粒子的随机反应扩散方法来实现，这种方法允许对细胞表面和细胞内蛋白质的运动和相互反应进行数值模拟。细胞的高分辨率软X射线断层图像将被重建，以提供免疫细胞之间界面的准确图像。根据这些图像重建的几何图形将被用于计算建模研究，以研究免疫细胞的激活如何依赖于细胞之间接触几何图形的结构，以及参与信号传递过程的蛋白质的物理性质。由于免疫细胞在人体对病原体和癌症的反应中发挥着关键作用，这类研究最终有可能进一步加深我们对疾病的理解和治疗。本项目调查细胞膜的形状和细胞质中的细胞亚结构如何改变细胞信号通路的预测动力学。这将通过开发新的基于粒子的随机反应-扩散(PBSRD)模型来实现，该模型以真实的T细胞细胞几何形状为基础，从X射线断层图像重建。这些研究将集中在T细胞信号通路上，其中基于膜的信号对T细胞在抗原刺激下的激活至关重要，并受到细胞质酶动态的高度调控。在这些途径中，膜的几何形状被认为通过微绒毛和丝状足细胞与抗原提呈细胞(APC)的相互作用而发挥重要作用。建模和成像研究的结合将给出定量的答案，即这些几何效应对T细胞信号的影响有多大。将开发四维空间随机模型，因为在细胞形状和内部亚结构可能显著影响信号通路行为的情况下，它们对于准确捕捉成功发挥作用的细胞信号过程的动力学是必要的。本项目的主要研究目标是：1)开发结合了分子表面扩散和反应的新型PBSRD。2)发展高效、精确的数值方法，对与PBSRD模型相关的空间跳跃过程进行采样。3)对T细胞和与APC结合的T细胞进行三维X射线断层成像研究，以了解T细胞内细胞形状、细胞器和物质密度的变化。4)将新的PBSRD方法应用于从成像研究中重建的3D几何图形，以研究细胞形状和细胞器障碍如何影响T细胞信号的动力学。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

To be able to predict and control the behavior of cells, it is necessary to understand how they detect, process and respond to external signals. This award will develop accurate and efficient numerical methods with which to study at the whole-cell scale how cells respond and process external signals. This will be done by developing new particle-based stochastic reaction-diffusion methods that allow the numerical simulation of the motion of, and reactions between, proteins on the surface of cells and within cells. High-resolution soft X-ray tomographic images of cells will be reconstructed to provide an accurate picture of the interfaces between immune cells. Geometries reconstructed from these images will then be used in computational modeling studies to investigate how the activation of immune cells depends on the structure of contact geometries between cells, and on physical properties of proteins involved in the signaling process. As immune cells play a key role in the body's response to pathogens and cancer, such studies have the potential to ultimately further our understanding and treatment of disease.This project investigates how both the shape of cell membranes, and cellular substructures within the cytosol, can modify the predicted dynamics of cell signaling pathways. This will be achieved by developing new particle-based stochastic reaction-diffusion (PBSRD) models in realistic cellular geometries of T cells, reconstructed from X-ray tomographic images. The studies will focus on T cell signaling pathways, where membrane-based signaling is critical for T cell activation in response to antigens, and highly regulated by the dynamics of cytosolic enzymes. In such pathways, membrane geometry is thought to play a major role through interactions of microvilli and filopodia with antigen presenting cells (APCs). The combination of modeling and imaging studies will give quantitative answers to the question of what the magnitude of these geometric effects are on T-cell signaling. Four-dimensional spatial stochastic models will be developed as they are necessary to accurately capture the dynamics of successfully functioning cellular signaling processes, in situations where cell shape, and internal substructure, can significantly influence the behavior of signaling pathways. The primary research objectives of this project are to: 1) Develop new PBSRD that incorporate the surface diffusion and reaction of molecules. 2) Develop efficient, exact numerical methods for sampling spatial jump processes associated with PBSRD models. 3) Conduct 3D X-ray tomographic imaging studies of T cells and T cells engaged with APCs to understand the variation in the shape of cells, organelles, and density of material within T cells. 4) Apply the new PBSRD methods in 3D geometries reconstructed from the imaging studies to investigate how cell shape and organelle barriers can influence the dynamics of T cell signaling.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.