| title | tags | authors | affiliations | date | bibliography | |||||||||||||||||||||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Tyssue: an epithelium simulation library |
|
|
|
2 december 2020 |
paper.bib |
The tyssue Python library seeks to provide a unified interface to implement bio-mechanical models of living tissues. Its main focus is on vertex based epithelium models. tyssue allows to model the mechanical behavior of 2D, apical 3D or full 3D epithelia based on the numerical resolution of the equations of motion for the mesh vertices. Biological processes are modeled through changes in the topological and dynamical properties of the mesh. tyssue is a modular library. Starting with the same tissue geometry, the choice of constraints, energy potential terms and parameters increases the possibility to answer different biological questions and easily explore mechanical hypotheses.
Tissue remodeling is a complex process integrating a large number of inputs such as gene expression pattern, cell adherent properties or cell mechanics. It can be difficult to manipulate specific aspects genetically. It can even be hard to simply capture, when the process takes only few minutes. Furthermore, morphogenesis is inherently a mechanical process. To execute complex morphogenetic movements, epithelia are driven by in-plane forces, like constriction of apical cell surface [@Heer:2017], and/or out-of-plane forces, such as the apico-basal cable in apoptotic cell [@Monier:2015; @Gracia:2019] or lateral tension [@Sherrard:2010; @Sui:2018]. Modeling these processes help us to understand how tissues acquire their shape, in complement of the experimental systems, and beyond their limitations. Several vertex models have been developed in the past few years to describe the physics of epithelia (for a review, see @Alt:2017), and common features can be identified. Several kinds of models have already been published. The apical vertex model has been used several times to study topology changes during morphogenetic movement in Drosophila, Hydra and Xenopus [@Staple:2010; @Farhadifar:2007; @Aegerter:2012]. Associated with protein dynamics, it has been used to study the effect of protein position on tissue organisation in zebrafish retina [@Salbreux:2012]. 3D vertex model have been used to study epithelium deformation due to normal development or to cancer development [@Okuda:2015; @Eritano:2020]. Most of the time, models are developed for a specific biological question and are difficult to adapt to other systems, for several reasons. However, there is some exception like Chaste [@Cooper:2020], which propose an open source C++ library to model cell populations or how specific events arise at the system level. With the tyssue library, we propose models which are adaptable and scalable with the field of research and the biological question. Topology and mechanics are implemented independently to improve the versatility of models.
The tyssue library defines epithelium as meshes. A vertex model defines a tissue as an assembly of vertices and edges, which can form polygonal face (in 2D) or polyhedron (in 3D). For now, we assume that cell junctions are straight lines. In tyssue, each edge is split, so that every face is limited by oriented "half-edges" (see figure 1 A), in a structure identical to the Linear Cell Complex in the CGAL library. The tyssue library allows to produce different kinds of tissue, from 2D to 3D tissue (see figure 1 B). The library implements concepts and mechanisms common to all vertex models, for both topological and mechanical aspects.
Figure 1: Description of tyssue geometry. A-Composition of a tissue from a vertex to a cell. B-Three kind of geometry that can be used in tyssue. C-Example of cell dynamics usable in 2D and 3D.
Common cellular processes are implemented in our library such as cell elimination, division or rearrangements. We implemented those processes based on previous works.
Cell division is modeled as the splitting of a cell by a straight line (or plane in 3D) [@Brodland:2002], the angle and position of the division plane can be decided (see Figure 1 C, right panel).
Changes in cell neighbors - also called rearrangements - happen when the size of the boundary between two neighboring cells passes below a certain threshold length in 2D (type 1 transition), or area in 3D (I-H or H-I transition) [@Okuda:2015]. In that case, the linked vertices fuse and are separated again, which can lead to a change in the local topology (see Figure 1 C, left panel).
Cell elimination happens when a cell area (volume) reaches a low threshold. When this happens, cell starts to lose contact with neighboring cells through series of rearrangements. Once the cell is reduced to a triangle (in 2D) or a tetrahedron (in 3D) the remaining vertices are merged to create a new vertex.
Although it was customary to assume the neighbor exchange to be a single-step process, we follow the work by Finegan et al. which describes cell exchange as a multistep, stochastic process [@Finegan:2019]. As a consequence, in tyssue, vertices are not limited to 3 (in 2D) or 4 (in 3D) linked edges, but can form "rosettes" - see type1 and rosette examples.
In tyssue, the dynamical behavior of epithelium is described by solving the equation of motions following Newton's principle. At the scales of the studied processes, the inertia is negligible compared to other forces such as friction, adhesion or contraction of the actin cytoskeleton.
Honda et al. assume that cell movements respond to mechanical forces in an overdamped manner and the vertices are driven by the sum of interfacial tension on cell boundaries and the resistance force against the deformation of cells [@Honda:1978; @Honda:1983]. The EulerSolver class in tyssue allows to simulate such an over-damped movement.
Interactions in the epithelium are described as potentials depending on the mesh geometry, as described in Farhadifar et al., who showed that a 2D epithelium geometry and topology can be faithfully reproduced by finding the quasi-static equilibrium of energy depending on cell areas and junction lengths [@Farhadifar:2007]. The QSSolver class allows to solve this gradient descent problem.
More recently, Bi et al. focused his work on tissue rigidity which allows or not cell displacement in an epithelium, based on the relation between area and perimeter of a cell [@Bi:2015]. In tyssue, it is easy to define custom terms of the potential, through an object oriented model "factory" design, and use them to solve either the over-damped or gradient descent problem.
This way, it is easy to test various combinations of energy terms and find those that best fit the observed in vivo dynamics.
Figure 2: Organisation of different part of tyssue
Documentation of the tyssue Python library can be found here. Notebook introduction on how to use tyssue library can be found here.
The tyssue library has already been used in several studies with different context of epithelia morphogenesis, such as leg folding and mesoderm invagination in Drosophila melanogaster [@Monier:2015; @Gracia:2019; @Martin:2021]. Github repository from those publications can be found here, here and here respectively.
The development of tyssue was supported by grants from the European Research Council (ERC) under the European Union Horizon 2020 research and innovation program (grant number EPAF: 648001), and from the Association Nationale de la recherche et de la Technologie (ANRT). tyssue has benefited from the contributions of Hadrien Mary, George Courcoubetis, Bertrand Caré and Félix Quinton.
We wish to thank all past and present members of Magali Suzanne's team for their continuous support and for providing valuable insight on epithelium biology, Cyprien Gay for the discussions on the physics of epithelia, and the scientific python community for the core tools [@Virtanen:2020; @Harris:2020; @Hunter:2007; @mckinney:2010] we use in this project.
Please contact [email protected]
tyssue is written in Python 3. Code and detailed installation instructions can be found here. Continuous integration is performed with Travis. The associated code coverage can be found at CodeCov.