Information flow in self-organized developmental systems

Embryonic development is a spectacular display of self-organization of multi-cellular systems, combining transformations of tissue mechanics and patterns of gene expression. These processes are driven by the ability of cells to communicate through mechanical and chemical signaling, allowing coordination of both collective movement and patterning of cellular states. To ensure proper biological function, such patterns must be established reproducibly, by controlling and even harnessing intrinsic and extrinsic fluctuations. While the relevant molecular processes are increasingly well understood, we lack principled frameworks to understand how tissues obtain information to generate reproducible patterns. I will discuss how combining dynamical systems models with information theory provides a mathematical language to analyze biological self-organization across diverse systems. Our approach can be used to define and measure the information content of observed patterns, to functionally assess the importance of various patterning mechanisms, and to predict optimal operating regimes of self-organizing systems. I will demonstrate how our framework reveals mechanisms of self-organization of in vitro stem cell systems in direct connection to experimental data, including intestinal organoids and gastruloids. This framework provides an avenue towards unifying the zoo of chemical and mechanical signaling processes that orchestrate embryonic development.

 Host: Linus Schumacher