Supervisor 1
Phillipe Roudot (philippe.roudot@univ-amu.fr) Institut Fresnel, ED184
Supervisor 2
Claudio Collinet (Claudio.collinet@univ-amu.fr) IBDM, ED62
Abstract
The ability of cells and tissues to change shape during development relies on patterns of force-transmitting molecules at the cell surface, such as adhesion molecules (e.g. E-Cadherin), that anchor and regulate cell contractions. Those patterns emerge from the dynamics of hundreds of intracellular organelles that transport adhesion molecules within the cell. Organelle dynamics can be observed in vivo through time-lapse fluorescence microscopy (Fig. 1A,B), however, the understanding of how their collective dynamics give rise to the observed patterns of cell adhesion has been limited by difficulties in measuring the complex motions of organelles in the noisy images typical of developing 3D tissues. In this project, we will build upon our recent breakthroughs in multi-particle tracking (MPT) to study how study of intracellular trafficking regulates patterns of adhesion during tissue morphogenesis. Specifically, we will combine the robustness of neural networks used in large language model (ChatGPT, Gemini etc …) and the interpretability of conventional Markov modeling to study the intracellular trafficking of E-cadherin during the epithelial morphogenesis in Drosophila embryos. The project will test the hypothesis that specific trafficking fluxes of E-cadherin sustain different cell shape changes and emerge from specific organization and dynamics of the endocytic system in the cell (Fig.1C,D).
Keywords
Tissue morphogenesis, intracellular trafficking, cell-cell adhesion
Multiple Object Tracking, Large Language Modeling, Markov Modeling.
Scientific question and Objectives
Computational perspective: The key challenge will be the robust measurement of unknown collective dynamics (endocytic organelle movements, fusion/fission events etc.) through photon-limited signals. To tackle this problem, we will shift the a priori knowledge from the biophysics to the information we have on the image formation process, the limitations of sensors and detectors, and the optical properties of the tissue. Based on our hybrid AI methods for MPT1, the main goal will be to generalize the training of a tracking transformer to endocytic events combined with the use of conventional Markov modeling for the validation and physical interpretation of results. One of the key challenges will be to ensure training convergence and scalability with an increasing number of objects in the field of view.
Biological perspective: The global trafficking kinetics of adhesion molecules depend on the local densities and dynamics of hundreds of individual organelles constituting the endocytic pathway. The key hypothesis addressed in this project is that different organization and collective dynamics of endocytic organelles underlie different types of cell and tissue morphogenesis (Fig. 1C-D). We first will infer the global E-cadherin trafficking rates (e.g. internalization, recycling, degradation) from endocytic organelles trajectories and then measure key differences in cells undergoing different types of morphogenetic events in the fly embryo during gastrulation.
Relevant references
R. Levayer, A. Pelissier-Monier, and T. Lecuit, “Spatial regulation of Dia and Myosin-II by RhoGEF2 controls initiation of E-cadherin endocytosis during epithelial morphogenesis,” Nat Cell Biol, vol. 13, no. 5, Art. no. 5, May 2011, doi: 10.1038/ncb2224.
R. Levayer and T. Lecuit, “Oscillation and Polarity of E-Cadherin Asymmetries Control Actomyosin Flow Patterns during Morphogenesis,” Developmental Cell, vol. 26, no. 2, pp. 162–175, Jul. 2013, doi: 10.1016/j.devcel.2013.06.020.
Sigismund, S., Lanzetti, L., Scita, G. & Di Fiore, P. P. Endocytosis in the context-dependent regulation of individual and collective cell properties. Nat. Rev. Mol. Cell Biol. 22, 625–643 (2021).
K. Granström, M. Fatemi, and L. Svensson, “Poisson Multi-Bernoulli Mixture Conjugate Prior for Multiple Extended Target Filtering,” IEEE Transactions on Aerospace and Electronic Systems, vol. 56, no. 1, pp. 208–225, Feb. 2020, doi: 10.1109/TAES.2019.2920220.
Y. Xie , H. Miao , J.T. Blankenship, « Membrane trafficking in morphogenesis and planar polarity », Traffic 2018 May 14:10.1111/tra.12580. doi: 10.1111/tra.12580
Relevant publications from the project advisors
P. Roudot et al., (2023) u-track3D: Measuring, navigating, and validating dense particle trajectories in three dimensions. Cell Reports Methods. Doi: 10.1016/j.crmeth.2023.100655.
Mishra, Piyush, and Philippe Roudot. “Comparative Study of Transformer Robustness for Multiple Particle Tracking without Clutter.” In EUSIPCO. Lyon, France, 2024. https://hal.science/hal-04619330.
Collinet C.*, Bailles A., Dehapiot B. and Lecuit T. “Mechanical regulation of substrate adhesion and de-adhesion drives a cell-contractile wave during Drosophila tissue morphogenesis”, Dev Cell 2024 Jan 8;59(1):156-172.e7. doi: 10.1016/j.devcel.2023.11.022. Epub 2023 Dec 15.
Bailles A., Collinet C., Philippe J-M., Lenne P-F., Munro E., Lecuit T. “Genetic induction and mechanochemical propagation of a morphogenetic wave” Nature 2019 Aug;572(7770):467-473. doi: 10.1038/s41586-019-1492-9.
