Professor Xu Guangkui's team at Xi'an Jiaotong University has developed an efficient discrete vertex simulation method based on the stiffness matrix of cellular micro-nanostructures and the force-chemical feedback loop of active molecules. This method is utilized to investigate the spatiotemporal evolution process of collective cell movement and deformation. The research findings were recently published in Nanotechnology Express.
Research Illustration (Image provided by the research team)
The research findings indicate that the discrete model is capable of quantitatively capturing some key features of diffusion in collective cell assemblies, including X-wave and cumulative intercellular stress. Additionally, the researchers demonstrated the model's ability to quantitatively capture different wave patterns, including the experimentally reported X-mode wave (normal epithelial cells) and V-mode wave (tumor epithelial cells), as well as a novel W-mode wave lying between the two. Importantly, the researchers revealed that the phase transitions between these wave patterns are controlled by the distribution of cellular forces. These findings provide new insights into the emergence, variation, and regulation of waves in dense cell layers.
The discrete simulation model developed by the research team, along with continuous theoretical approaches, can quantitatively capture the emergent behavior of cell population movement. It has been revealed that the distribution of cellular forces regulates the phase transitions between wave patterns (X, V, and W modes). These findings underscore the influence of local cellular geometric features and mechanical properties on the movement and deformation of entire tissues. During development and wound healing processes, transitions in local cell density and contractility have the potential to guide tissue repair and regeneration. In the case of tumor tissues, these mechanisms may be manipulated by cancer cells to enhance their invasive capabilities. Meanwhile, emergent phenomena such as multicellular waves can reflect local changes in cell populations.
For more information, please refer to the related paper: https://doi.org/10.1021/acs.nanolett.3c04876
