Abstract

The ability of cells and tissues to change shape during development relies on patterns of molecules at the cell surface, such as adhesion molecules and signaling receptors, that anchor and regulate cell contractions. These processes emerge from the collective dynamics of hundred-to-thousand agents (molecules, polymers, molecular motors, cellular organelles etc.) which can be observed in vivo through time-lapse fluorescence microscopy. However, the stochastic nature of the interactions amongst the agents challenges our understanding of how cellular functions emerge from their collective dynamics. This project proposal aims at using image time series to probe the non-linear link between the recruitment of thousands of interacting molecules, the robust molecular patterning that emerges and the tight orchestration of contractile events.

Specifically, the project will focus on a data-driven study of endo/exocytosis (E/E), a process that endows the cell with a capacity to exchange and redistribute molecules at the cell surface. Through the collective dynamics of hundreds of membrane intracellular organelles, E/E allows cells to establish and maintain spatial patterns of adhesion and signaling molecules which, in turn, regulate cellular contractility. How E/E is regulated and in turn regulates tissue morphogenesis is still largely unknown due to the challenge of tracking and measuring the dynamics of hundred-to-thousands organelles in noisy images. This project will be based our recent work on non-supervised multiple object tracking and large language modeling of intracellular dynamics to drive the calibration of 3D confocal imaging experiment and optimize the quantification of molecular events. By parameterizing both the image formation process and the multiscale biological interactions, these approaches will help decipher how cells recruit, deplete, and translocate molecules to maintain spatial patterns that are crucial to shape formation.