ERA-CAPS - Appel Europe-USA pour renforcer la recherche transnationale en biologie moléculaire végétale

From genes to shape-Towards development of a computable flower – Genes2Shape

From Genes to Shape : modelling early flower development

The project is aimed at understanding how molecular regulation integrates with mechanics to control plant shape, a problem with wide implications for both fundamental and applied biology. We will address this issue in the Arabidopsis flower, which is amongst the best characterized systems in plant developmental biology. Using a pluridisciplinary aproach, we will integrate information from multiple scales, from molecular networks to physical properties and geometry into a single picture.

The development of the computable flower as a tool for mechanistic analysis

From a mechanistic point of view, it is widely accepted that regulatory molecular networks interfere with the properties of the structural cellular elements (cell wall, cytoskeleton) to induce particular growth patterns. How this occurs and how this is coordinated in space is not known. To obtain a mechanistic understanding of such a complex process, information from multiple scales, from molecular networks to physical properties and geometry have to be combined into a single picture. An integrated tool to do so is currently not available. <br />We will address this issue in the Arabidopsis flower. A tool, called the “Computable Flower” will be developed that permits (i) integration of data on geometry, gene expression and biomechanics and (ii) the user to explore, interpret and generate hypotheses <br />The Computable Flower will be populated with existing or novel quantitative datasets coming from experimental and computational techniques concerning: <br />(i) the spatial distribution of regulatory molecules such as transcription factors and hormones.<br />(ii) the spatial expression patterns of genes involved in cell wall synthesis. <br />(iii) the spatial organisation and properties of structural elements, including cell wall stiffness, cytoskeleton and cellulose microfibril organisation. <br />(iv) changes in geometry. <br />We will develop computational models to generate hypotheses regarding biochemical, physical and geometrical properties with simulation outcomes quantitatively compared with experimental data. Predictions coming from the modelling will guide experiments using domain-specific perturbation of genes that influence microtubule and wall status. These transgenic lines will then be subjected to detailed quantitative growth studies to test the validity of the model or to refine it. <br />The above measured datasets and simulation outcomes will be disseminated via an interactive graphical web interface of the Computable Flower.

(1) set up an interactive tool called the “Computable Flower” that integrates for the first time spatial and temporal information on molecular regulators, quantitative data on morphometrics, and maps of physical parameters. This information will come from both experiments and simulations.
(2) generate finite element models of different floral stages. Simulations will formalize hypotheses concerning gene expression and mechanical (wall) properties to changes in morphology.
(3) perform model-guided experiments to test the validity of the model predictions. We will perform spatio-temporal perturbation of cell wall components using domain specific inducible miss-expression of genes that influence microtubule organization and pectin status.
(4) allow visualization of data and simulation outcomes of the computable flower available via a web based interactive graphical interface.

We so far developed a first web-based version of a 4D reconstruction of an Arabidopsis flower. This was done using Morphonet (http://www.morphonet.org), a tool developed by the group of Christophe Godin at the RDP. Morphonet is a web-based interactive platform for visualization and sharing of complex morphological data and metadata. Exploiting its Unity (https://unity.com) 3D visual engine, it offers a vast assortment of possible interactions with 2, 3 and 4D datasets. Through a flexible hierarchical representation of biological structures and dedicated formats for associated metadata, users can follow the dynamics of biological shapes, onto which associated quantitative and qualitative properties can be projected. The flower template was introduced in Morphonet, and subsequently data concerning growth rates, growth directions and gene expression were added.

Halfway the project, the main objective was to increase the amount of data included in the computable flower and to develop mechanical models.

Several publications submitted.

This project is aimed at understanding how molecular regulation integrates with mechanics to control overall plant shape, an unresolved problem with wide implications for both fundamental and applied biology. We will address this issue in the Arabidopsis flower, which, besides their obvious importance as reproductive structures, are amongst the best characterised systems in plant developmental biology.
From a mechanistic point of view, it is widely accepted that regulatory molecular networks interfere with the properties of the structural cellular elements (cell wall, cytoskeleton) to induce particular growth patterns. How this occurs and how this is coordinated in space is not known. To obtain a mechanistic understanding of such a complex process, information from multiple scales, from molecular networks to physical properties and geometry have to be combined into a single picture. An integrated tool to do so is currently not available.
Building on our complementary experience in interdisciplinary research on plant development, we will therefore develop a tool, called the “Computable Flower” that permits (i) integration of data on geometry, gene expression and biomechanics and (ii) the user to explore, interpret and generate hypotheses based on data supported by mechanistic modelling approaches. The tool therefore provides an integrated description in the form of a 3D dynamic template of the growing flower bud.
The Computable Flower will be populated with existing or novel quantitative datasets coming from experimental and computational techniques concerning:
(i) the spatial distribution of regulatory molecules such as transcription factors and hormones.
(ii) the spatial expression patterns of genes involved in cell wall synthesis and remodelling which operate downstream from these regulatory networks.
(iii) the spatial organisation and properties of structural elements, including cell wall stiffness, cytoskeleton and cellulose microfibril organisation.
(iv) changes in geometry.
In the process we will develop computational models to generate hypotheses regarding biochemical, physical and geometrical properties with simulation outcomes quantitatively compared with experimental data. Predictions coming from the modelling will guide experiments using domainspecific perturbation of genes that influence microtubule and wall status. These transgenic lines will then be subjected to detailed quantitative growth studies to test the validity of the model or to refine it. The above measured datasets and simulation outcomes will be disseminated via an interactive graphical web interface of the Computable Flower, transforming the way data is provided to the community by integrating multiple data types and allowing users to browse the data and build their experiments and models on the latest information and insights. Importantly, the tools generated to create the computable flower will be easily adaptable to a wide range of plant and animal systems.

Project coordination

Jan Traas (REPRODUCTION ET DEVELOPPEMENT DES PLANTES)

The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.

Partner

RDP REPRODUCTION ET DEVELOPPEMENT DES PLANTES

Help of the ANR 186,999 euros
Beginning and duration of the scientific project: March 2018 - 36 Months

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