No abstract

Computational models have great potential to accelerate bioscience, bioengineering, and medicine. However, it remains challenging to reproduce and reuse simulations, in part, because the numerous formats and methods for simulating various subsystems and scales remain siloed by different software tools. For example, each tool must be executed through a distinct interface. To help investigators find and use simulation tools, we developed BioSimulators (https://biosimulators.org), a central registry of the capabilities of simulation tools and consistent Python, command-line and containerized interfaces to each version of each tool. The foundation of BioSimulators is standards, such as CellML, SBML, SED-ML and the COMBINE archive format, and validation tools for simulation projects and simulation tools that ensure these standards are used consistently. To help modelers find tools for particular projects, we have also used the registry to develop recommendation services. We anticipate that BioSimulators will help modelers exchange, reproduce, and combine simulations.

Morphogenesis, wound healing and some cancer metastases depend upon migration of cell collectives that need to be guided to their destination as well as coordinated with other cell movements. During zebrafish gastrulation, extension of the embryonic axis is led by the mesendodermal polster that migrates towards the animal pole, followed by axial mesoderm that is undergoing convergence and extension. We here investigate how polster cells are guided towards the animal pole. Using a combination of precise laser ablations, advanced transplantations and functional as well as in silico approaches, we establish that the directional information guiding polster cells is mechanical, and is provided by the anteriorward migration of the following cells. This information is detected by cell-cell contact through E-Cadherin/-Catenin mechanotransduction and propagates from cell to cell over the whole tissue. Such guidance of migrating cells by followers ensures long-range coordination of movements and developmental robustness.

Morphogenesis, wound healing and some cancer metastases depend upon migration of cell collectives that need to be guided to their destination as well as coordinated with other cell movements. During zebrafish gastrulation, extension of the embryonic axis is led by the mesendodermal polster that migrates towards the animal pole, followed by axial mesoderm that is undergoing convergence and extension. We here investigate how polster cells are guided towards the animal pole. Using a combination of precise laser ablations, advanced transplantations and functional as well as silico approaches, we establish that the directional information guiding polster cells is mechanical, and is provided by the anteriorward migration of the following cells. This information is detected by cell-cell contact through E-Cadherin/α-Catenin mechanotransduction and propagates from cell to cell over the whole tissue. Such guidance of migrating cells by followers ensures long-range coordination of movements and developmental robustness.

Collective cell migration is an important process during biological development and tissue repair, but may turn malignant during tumor invasion. Mathematical and computational models are essential to unravel the mechanisms of self-organization that underlie the emergence of collective migration from the interactions among individual cells. Recently, guidance-by-followers was identified as one such underlying mechanism of collective cell migration in the zebrafish embryo. This poses the question how guidance stimuli are integrated when multiple cells interact simultaneously. Here, we extend a recent individual-based model by an integration step of the vectorial guidance stimuli and compare model predictions obtained for various variants of the mechanism (arithmetic mean of stimuli, dominance of stimulus with largest transmission interface, dominance of most head-on stimulus). Simulations are carried out and quantified within the modeling and simulation framework Morpheus. Collective cell migration is found to be robust and qualitatively identical for all considered variants of stimulus integration. Moreover, this study highlights the role of individual-based modeling approaches for understanding collective phenomena at the population scale that emerge from cell-cell interactions.

Collective cell migration is an important process during biological development and tissue repair but may turn malignant during tumor invasion. Mathematical and computational models are essential to unravel the mechanisms of self-organization that underlie the emergence of collective migration from the interactions among individual cells. Recently, guidance-by-followers was identified as one such underlying mechanism of collective cell migration in the embryo of the zebrafish. This poses the question of how the guidance stimuli are integrated when multiple cells interact simultaneously. In this study, we extend a recent individual-based model by an integration step of the vectorial guidance stimuli and compare model predictions obtained for different variants of the mechanism (arithmetic mean of stimuli, dominance of stimulus with largest transmission interface, and dominance of most head-on stimulus). Simulations are carried out and quantified within the modeling and simulation framework Morpheus. Collective cell migration is found to be robust and qualitatively identical for all considered variants of stimulus integration. Moreover, this study highlights the role of individual-based modeling approaches for understanding collective phenomena at the population scale that emerge from cell-cell interactions.

Computational models have great potential to accelerate bioscience, bioengineering, and medicine. However, it remains challenging to reproduce and reuse simulations, in part, because the numerous formats and methods for simulating various subsystems and scales remain siloed by different software tools. For example, each tool must be executed through a distinct interface. To help investigators find and use simulation tools, we developed BioSimulators (https://biosimulators. org), a central registry of the capabilities of simulation tools and consistent Python, command-line, and containerized interfaces to each version of each tool. The foundation of BioSimulators is standards, such as CellML, SBML, SED-ML, and the COMBINE archive format, and validation tools for simulation projects and simulation tools that ensure these standards are used consistently. To help modelers find tools for particular projects, we have also used the registry to develop recommendation services. We anticipate that BioSimulators will help modelers exchange, reproduce, and combine simulations.