Collaborative Research: Computational Methods for Understanding the Influence of Cellular Geometry and Substructure on Signaling

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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.