EndoEmbryo: Understanding how endo/exocytic fluxes shape embryo morphogenesis
Tissue morphogenesis relies on spatial patterns and polarity of cell surface molecules, such as adhesion molecules, signaling receptors and actomyosin contractility. Trafficking by endo/exocytosis (E/E) endows the cell with a capacity to exchange molecules with the outside and to polarize cell surface protein distribution and signaling. How E/E is exploited to generate patterns of signaling and adhesion molecules at the cell surface and in turn regulates actomyosin contractility to drive morphogenesis is still unknown. This project aims at explaining how E/E fluxes of relevant adhesion molecules and signaling receptors are regulated to control cell mechanics during tissue morphogenesis in the fly embryo. We will probe this complex system by measuring the spatial distribution and the dynamic of E/E events as well as correlating them to patterns of actomyosin contractility and cell morphogenesis. To tackle the challenge in measuring hundreds-to-thousands of E/E processes in sequences presenting complex multifactorial dynamics, we will combine 3D confocal imaging at high framerate with novel multiple target tracking methods under constrains of low photon count. This will be completed with a parameterization of the cell membrane dynamics to study the coordination of E/E spatial patterning and its role in morphogenetic pathways.
Tissue morphogenesis, intracellular trafficking, actomyosin contractility, stochastic filtering, multiscale modeling.
The first objective will consist in developing an integrated computational and experimental framework to measure the spatial distribution of E/E fluxes of cell adhesion molecules (E-cad and Integrins) and signalling receptors (GPCRs) in two distinct contexts of morphogenesis in the fly embryo. This framework will then be applied to: 1) characterize any heterogeneity in endocytic particle dynamics relative to cell adhesion molecules and GPCRs surface distributions, and 2) to detect any temporal hierarchy between endocytic events and patterns and dynamics of actomyosin contractility during moprhogenesis.
Proposed approach (experimental / theoretical / computational)
Living embryos will be imaged by spinning disk confocal microscopy to track endocytic events in 3D over time. Markers of endocytosis (Clathrin, AP-2) and of exocytosis (Sec5, Sec15) will be imaged together with relevant cell adhesion molecules (E-Cad and Integrins) and signalling receptors (GPCRs) as endocytic cargo in two tissues undergoing different types of morphogenetic events. Actomyosin contractility and cell shape will be monitored to correlate endocytic events to cell and tissue morphogenesis. The quantification of endocytic turn over is based on a stochastic modeling of both the biophysical process of clathrin-coated pits formation and the noisy nature of fluorescence imaging. In order to compensate for the multi-scale nature of epithelial motion that challenges the tracking of an object from one frame to the next, we will propose a new approach that enables the decrease of apparent motion magnitude by increasing the framerate/SNR ratio. This regime of acquisition requires the registration of many false targets in combination with our targets of interest (the endocytic pits). By combining a Poisson point-process model for clutter with a Bernouilli modeling of target detections, will develop sensitive and scalable approaches for the detection and measurement (with associated uncertainty) of endocytic events. This approach will be completed with a stochastic modeling and inference of the temporal hierarchy between molecular events (endocytosis, adhesion recruitment, actomyosin mecanics) and causal effect to some degrees as described by Granger Causality principles.
The PhD student will be deeply involved in an interdisciplinary conversation with different expertise in computer vision, cellular biology, biochemistry and microscopy. First, the optimal alignment of techniques must be explored to optimize the measure of molecular events at scale: setting the blueprint for optimal fluorescent labelling, illumination level and sampling adjustment as well as algorithm selection and parameterization. Second, the design of the motion model must be chosen as a trade-off between physical accuracy and computational feasibility, requiring strong mentoring in complex systems physics and computer vision. Similarly, the interpretation of biological measurements across scales to understand signaling pathways and setting the next experiment also requires expertise in cellular and system biology. Finally, the development of perennial tools to study those complex 3D systems involves significant training in numerical methods for stochastic inferences.
The PhD student will have a formal training in applied mathematics or computer science with a keen interest in biophysics, cell biology and the study of complex systems.
Is this project the continuation of an existing project or an entirely new one? In the case of an existing project, please explain the links between the two projects
It is a follow up study on a preliminary benchmark on tracking approach for the developing embryo.
2 to 5 references related to the project
- R. Levayer, et al . Nat Cell Biol, vol. 13, no. 5, Art. no. 5, May 2011,
- R. Levayer and T. Lecuit, Developmental Cell, vol. 26, no. 2, pp. 162–175, Jul. 2013,
Sigismund, et al Nat. Rev. Mol. Cell Biol. 22, 625–643 (2021).
- K. Granström et a IEEE Trans on Aerospace and Electronic Systems, vol. 56, no. 1, pp. 208–225, Feb. 2020
3 main publications from each PI over the last 5 years
Roudot et al. “U-Track 3D: Measuring and Interrogating Intracellular Dynamics in Three Dimensions.” BioRxiv. 2022.
M. L. Azoitei et al., “Spatiotemporal dynamics of GEF-H1 activation controlled by microtubule- and Src-mediated pathways,” J Cell Biol, vol. 218, no. 9, pp. 3077–3097, Sep. 2019, doi: 10.1083/jcb.201812073.
Roudot et al. , “Piecewise-Stationary Motion Modeling and Iterative Smoothing to Track Heterogeneous Particle Motions in Dense Environments.” IEEE Transactions on Image Processing. 2017.
Collinet C. and Lecuit T. “Programmed and self-organized flow of information during morphogenesis.” Nat Rev Mol Cell Biol. 2021 Apr;22(4):245-265. doi: 10.1038/s41580-020-00318-6.
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.
Collinet C, Rauzi M, Lenne PF, Lecuit T. “Local and tissue-scale forces drive oriented junction growth during tissue extension” Nat Cell Biol 2015 Oct;17(10):1247-58. doi: 10.1038/ncb3226.