Image-based Modeling and Simulation of Morphogenesis

Asadullah1, Sandeep Kumar2,Shamik Sen1 1Indian Institute of Technology Bombay, Mumbai, India. 2Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, University of Toronto, Ontario, Canada. Email:shamiks@gmail.com Genetically, epigenetically and phenotypically cancer cells are known to be heterogeneous. While a plethora of studies have focused on genetic heterogeneity, very few studies have probed phenotypic heterogeneity in these cells, how such heterogeneity emerges, and the consequences of such heterogeneity vis-à-vis cancer invasion. We hypothesize that the buildup of compressive forces during initial tumor formation leads to emergence of phenotypically distinct sub-populations. To test this, we have developed a computational model using Cellular Potts model (CPM), wherein we track the growth of a tumor within a confined region from a single cell incorporating cell division, cell migration and cell death within the confined region.Assuming a simple time and area-dependent cell division rule, we show that temporal reduction in space owing to cell division leads to generation of cells which are both smaller and softer than the starting cell. Ongoing studies are evaluating the implication of such heterogeneity on invasion patterns as well as experimentally testing the predictions of our model.

Computational modeling and simulation become increasingly important to analyze tissue morphogenesis. A number of corresponding software tools have been developed but require scientists to encode their models in an imperative programming language. Morpheus (1,2), on the other hand, is an extensible open-source software framework that is entirely based on declarative modeling. It uses the domain-specific language MorpheusML to define multicellular models through a user-friendly GUI and has since proven applicable by a much broader community, including experimentalists and trainees. We here present how MorpheusML (3) and the open-source framework (4) allow for advanced scientific work-flows. MorpheusML provides a bio-mathematical language in which symbolic identifiers in mathematical expressions describe the dynamics of and coupling between the various model components. It can represent the spatial aspects of interacting cells and follows the software design rule of separation of model from implementation, enabling model sharing, versioning and archiving (3). A numerical simulation is then composed by automatic scheduling of predefined components in the simulator. Moreover, Morpheus supports simulations based on experimental data, e.g. segmented cell configurations, and offers a broad set of analysis tools to extract features right during simulation. A rich c++ API allows to extend MorpheusML and the simulator with user-tailored plugins. Finally, we apply Morpheus and image-based modeling to study the regulatory mechanisms underlying liver tissue architecture and flatworm regeneration (5). (1) Starruß et al. Morpheus: a user-friendly modeling environment for multiscale and multicellular systems biology. Bioinformatics 30, 1331, 2014. (2) Homepage: https://morpheus.gitlab.io (3) Model repository: https://imc.zih.tu-dresden.de/wiki/morpheus/doku.php?id=examples:examples (4) Open source code: https://gitlab.com/morpheus.lab/morpheus (5) Vu et al. Multi-scale coordination of planar cell polarity in planarians. BioRxiv 324822, 2018. Co-Authors: Jörn Starruß(1), Walter de Back(2), Andreas Deutsch(1), Lutz Brusch(1) (1) Center for Information Services and High Performance Computing (ZIH), (2) Institute for Medical Informatics and Biometry (IMB), TU Dresden, Germany

Keisuke Ishihara1,2,3, Elena Gromberg4, Marta N. Shahbazi5, Magdalena Zernicka-Goetz5, Jan F. Brugués1,2,3, Frank Jülicher2,3, Elly M. Tanaka4 1 Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany 2 Max Planck Institute for the Physics of Complex Systems, Dresden, Germany 3 Center for Systems Biology Dresden, Dresden, Germany 4 Research Institute of Molecular Pathology, Vienna, Austria 5 University of Cambridge, Cambridge, UK Abstract: The epithelium is a fundamental tissue architecture that lines the outer surfaces of many organs and inner cavities within them. While past studies have demonstrated how local differences in cell mechanical properties induce epithelial folding, the topology of epithelial surfaces has not been addressed. What are the cell biological and physical conditions that determine whether an epithelium remains connected, or divides into multiple, topologically distinct epithelia? To address this issue, we study neuroepithelium formation by differentiating free-floating 3D aggregates of mouse embryonic stem cells. Within 4 days, a continuous apical membrane domain forms in the interior of the tissue as a result of collective cell polarization and epithelialization. Treatment with retinoic acid induces the apical membrane to split up into multiple spherical structures, or fluid-filled cysts. We hypothesize that apical surface area and its topology are controlled by retinoic acid-mediated down regulation of PODXL, an apical membrane protein with a negatively charged extracellular domain. Indeed, PODXL heterozygote cells show fragmented apical surfaces in the absence of retinoic acid, and PODXL overexpression show continuous epithelium overcoming the effect of retinoic acid. Neutralizing the negative charge in the system mimics the effect of PODXL reduction, underscoring the importance of electrostatic charge in apical membrane mechanics. We develop a biophysical framework based on vertex model of tissue mechanics that predicts cell shape and epithelial topology from the abundance of apically localized, charged membrane proteins. Thus, we elucidate the cell biological basis for retinoic acid-mediated morphogenesis, and propose that epithelial self-organization can be conceptually understood in analogy to the topological transitions of surfactant self-assembly.

A key challenge for the future of computational modelling is how to easily share complex image-driven simulations between a diverse community of theoreticians and experimentalists. This is essential so that different researchers can test and compare each others’ hypotheses, and to allow their new results to build on the previous results of others. We present our new modelling platform LIMB-NET, an openly accessible online simulator for intuitive image-based computational modelling, simulation, and visualisation of gene expression patterns crucial to limb development. LIMB-NET will allow remote users to upload and share the spatiotemporally-varying expression patterns of genes relevant to limb development throughout different stages of morphogenesis, mapping them onto a previously published standarised computational description of limb growth. LIMB-NET will incorporate three key functionalities, permitting researchers in the field of limb development to: 1) browse a database of existing known 2D gene expression patterns across a range of time points during early limb development 2) upload their own gene expression patterns, e.g., from WMISH, immunostaining, or other images, align the images based on developmental stage, and map the patterns into the modelling framework 3) straightforwardly formulate, simulate and compare computational models of gene regulatory networks In LIMB-NET, 2D gene expression patterns taken from images are mapped into a standard morphological framework, the ‘morphomovie’, covering the developmental stages E9.5 to E12.5 of mouse hindlimb bud. LIMB-NET’s customisable models are based on a reaction-diffusion framework simulated using finite-volume techniques on a moving finite element mesh. The models can use the experimental data stored in morphomovies as inputs. Expression patterns predicted by a given computational model can be visualised in the same morphomovie framework as experimentally acquired data, permitting a direct comparison to be made between the two, or indeed between outputs of different models. Most importantly, all this functionality will be accessible through a standard web browser, avoiding the need for any special software, and thus opening the field of image-driven modelling to the full diversity of the scientific community.