Team, Visitors, External Collaborators
Overall Objectives
Research Program
Highlights of the Year
New Software and Platforms
New Results
Partnerships and Cooperations
XML PDF e-pub
PDF e-Pub

Section: New Results

Dynamical characterization of morphogenesis at cellular scale

Participants : Guillaume Cerutti, Emmanuel Faure [External Collaborator] , Christophe Godin, Anuradha Kar, Bruno Leggio, Jonathan Legrand, Patrick Lemaire [External Collaborator] , Grégoire Malandain [External Collaborator] , Florent Papini, Manuel Petit, Jan Traas [External Collaborator] .

The modeling of morphogenesis requires to explore the interconnection of different spatial and temporal scales of developing organisms. Non-trivial questions such as whether the observed robustness of morphogenesis is rooted in some highly conserved properties at the cellular level or whether it emerges as a macroscopic phenomenon, necessitate precise, quantitative analyses of complex 3D dynamic structures. The study of dynamical properties at the cellular scale poses at the same time key technical challenges and fundamental theoretical questions. An example of the former category is how to characterize and follow the change of shape of cells within tissues and of tissues within organs, and how to couple this change with, for instance, gene expression dynamics; an illustration of the latter is how to define cell-scale variability of morphogenesis within and between species.

Our team has produced this year several results in this context:

Cell-scale atlases of development. One fundamental question linked to morphogenesis is at which level and timescale tissue or organ development is reproducible and stereotyped. To answer this question, variability must be quantitatively assessed. In the team we have created to this end two morphogenetic atlases: the atlas of gene expression patterns in the Arabidopsis thaliana flower development and the atlas of early embryonic development of the ascidian Phallusia mammillata.

Thanks to the invariant cellular lineage of early development of P. mammillata embryos and to 3D reconstruction of their development at cellular resolution, quantitative comparison of their properties from cell to tissue scale has been performed. After fluorescent membrane labelling, several embryos have been imaged for several hours by light-sheet microscopy. These images were then reconstructed through the segmentation pipeline ASTEC, which also automatically tracked each cell over several rounds of cell division. This large amount of data allowed us to create an atlas of geometrical and topological properties at cellular resolution, which gives unprecedented depth of information on the variability of ascidian development. In addition this atlas, coupled to previous knowledge on gene-expression dynamics from the ascidian genetic database (ANISEED), made it possible for us to develop a mathematical and computational model to explore the main drivers of early ascidian development, identified as area-of-contact-mediated cell-cell communications. This model was also validated by experimental manipulations and mutations induced in ascidian embryos. This work is currently under review [26].

On the other hand, developing digital atlases of organism or organs development is a complex challenge for organisms presenting a strong variability in the cellular layout. Indeed contrary to C. Elegans or P. mammillata, for instance, that posses a very strict cell lineage in early phases, the development of most plant organs is under the influence of robust genetic patterns without a unique cellular layout. In that respect, proposing a cell-based atlas of flower development for instance is not straightforward and specific methods have been developed to choose a representative examples of the developing Arabidopsis thaliana flower. Using this representative flower we have generated an atlas in which we have introduced manually the expression patterns of 27 genes. The knowledge generated by the creation of this atlas makes it possible to have a first quantitative (correlative) view on the relation between gene activity and growth.

Robustness of ascidian embryonic development. The image segmentation pipeline ASTEC developed by the team in collaboration with the Inria Morpheme project-team in Sophia Antipolis and the CRBM team in Montpellier, allows the 3D reconstruction and tracking of each cell during early ascidian embryogenesis. This methods allowed us to reconstruct over 50 ascidian embryos, both wild-type and mutants. Exploiting this large database and the fixed cellular lineage of ascidian embryos, we extracted and compared geometrical and topological cellular properties. This allowed us to compare the intra-embryonic (left/right) to the inter-embryonic level of variability of several properties, including cell volume, cell-cell contacts and the structure of the tree seeded by each cell. This study demonstrated that the genetic-induced variability is comparable to the stochastic one, quantitatively showing that ascidian embryonic development is highly canalized, and that the high reproducibility of shapes observed during embryogenesis is rooted in the robustness of cellular geometry and topology. To look for the origin of this canalisation, we developed a mathematical model exploiting our quantitative geometric database and the previously-existing ascidian genetic database ANISEED. This model suggests that the main driver of ascidian development is the cell-cell communication mediated by direct physical contact, and hence dependent of the area-of-contact between neighbouring cells. This means that the robustness of cell topology and geometry is necessary for cell-cell biochemical interactions to give rise to the correct fate restriction events, which in turn we showed to be responsible for major changes of embryo geometry. We also tested and validated this feedback loop between cell contacts, fate restriction events and embryonic geometry predicted by the model by manipulations and mutations induced in ascidian embryos.These results are reported in a paper which is currently under review [26].

Robust extraction and characterization of cellular lineages. The quantification of temporal properties at cellular scale such as volumetric growth rate or strain patterns relies extensively on the identification of cellular lineages in time-lapse acquisitions of living tissues. In the case of plant tissues where the deformations between two consecutive time points can be very important in post-embryonic morphogenesis processes such as early flower development, it remains a real challenge to compute those lineages automatically, and manual user annotation is generally required to produce reliable results.

Building on the previous expertise of the team [25], [28] and on the state-of-the-art computational library for image analysis, timagetk, developed in collaboration with the Morpheme team, we currently develop a set of robust automatic cell lineaging methods for cases ranging from small to highly non-linear deformations. In the course of a M2 internship and the first months of a starting PhD work (Manuel Petit), a first so-called “naive” lineaging method has been implemented and validated on synthetic data with limited deformations. Methods involving optimal flow algorithms on graph structures and iterative image registration are being developed to provide robust results in the case of faster growing tissues. The output of these methods will allow to use the tools developed by the team for the analysis of spatio-temporal properties of growing cells at a much larger scale. This work is part of the Inria IPL Naviscope.

Reconstruction of Arabidopsis ovule development. The ovule is a relatively simple organ, with limited developmental variability, which makes it an excellent case study for the computational modeling of organ development. Given the technical difficulty of producing live-imaging acquisition sequences of ovules, we developed a method to perform a spatial registration of multiple individual ovules at various developmental states and in different global poses. Using the global cylindrical symmetry of the organ and the surface curvature as a key geometrical feature, we aligned individuals on their main axes and on their junction with the underlying placental tissue. Jointly with the 3D segmentation of cells in images, this will allow to evidence the invariant features of ovule development at cellular scale, and to study the robustness of the dynamics of the megaspore mother cell (MMC) across indivduals. This work was part of the Imago project.