Information flow in developmental cell fate patterning

Embryonic development relies on the ability of multi-cellular systems to collectively coordinate the establishment of precise spatial patterns of cell fates. An inevitable obstacle to such coordination is intrinsic noise at the single-cell level, which constrains the amount of information accessible to cells for fate decisions. While such information was often considered to be encoded in overall concentrations of extracellular signals, it is becoming increasingly clear that cells use a much broader set of inputs to make decisions. In this project, we will develop a new data-driven theoretical framework of developmental patterning to quantify, characterize and predict how cells generate and process four types of information: dynamical signals, neighborhood interactions, tissue heterogeneity, and mechanical information. We will establish a novel theoretical methodology by uniting computational tissue models that account for single-cell noise with information theory to bridge the scales and relate mechano-chemical inputs to cell fate decisions. We will develop this approach in direct connection with spatio-temporal imaging experiments in two model systems. First, we will determine how regulatory interactions in 2D human gastruloids generate information encoded in complex signaling dynamics, and how single cells can use this information to decide their fate. Second, we will reveal how signaling and mechanics interplay to establish mechano-chemical information in intestinal organoids, driving simultaneous fate patterning and tissue morphogenesis. This project will uncover how cell-cell interactions establish self-organized spatial patterns that relay information accessible to single cells to reliably instruct cell fate decisions, and give insight into the fundamental constraints under which developmental systems operate.