Cell-based modelling of mechanical crosstalk between cells and networks of extracellular matrix fibers
Cell self-organization into higher-order structures bridges subcellular, cellular, and multicellular scales. Mechanical forces can act across these scales, and cells can sense long-ranged mechanical signals from distant neighbors. In animal tissues, mechanical forces are transmitted via an interconnected network of fibrous proteins that are part of the extracellular matrix (ECM). Cell-based models (also known as agent-based or individual-based models) represent cells as spatially discrete entities physically interacting through forces or energy potentials. To incorporate the mechanics of the ECM, cell-based models are frequently hybridized with partial differential equation models of the ECM’s material properties. However, as this approach assumes substrate homogeneity, it struggles to represent the mechanics of anisotropic fibrous ECM networks.
I will present joint work where we addressed this limitation by combining two modelling frameworks – the cell-based cellular Potts model for cells, and a bead-spring molecular dynamics model for ECM fibers. As a case study, we model a classical biomechanical experiment consisting of an isolated contractile cell embedded in a fiber network. We demonstrate how several parameters including fiber number, fiber crosslinks, and number of cell-ECM adhesions affect network strain and local fiber density, showing that the underlying dynamics of the model suffice to reproduce published experimental observations. Our model captures essential features of cell-ECM interactions including heterogeneous force transmission through the network and mechanical crosstalk between distant cells. I will discuss how the model can be used to study the emergence of complex multicellular behavior from mechanical crosstalk with the ECM, e.g., during blood vessel formation.