Biophysical Society Thematic Meeting | Ascona 2026

Mechanobiology of Infection

Poster Abstracts

1-POS Board 1 MODELING BIOPHYSICAL FORCES AND CELLULAR BEHAVIOR USING DELAUNAY-OBJECT-DYNAMICS Zoya Amjad 1 ; Sebastian C. Binder 1 ; Michael Meyer-Hermann 1,2,3 ; 1 Helmholtz Centre for Infection Research (HZI), Department of Systems Immunology (SIMM), Braunschweig Integrated Centre of Systems Biology (BRICS), Braunschweig, Germany 2 Technische Universität Braunschweig, Institute for Biochemistry, Biotechnology and Bioinformatics, Braunschweig, Germany 3 Lower Saxony Center for Artificial Intelligence and Causal Methods in Medicine (CAIMed), Hannover, Germany In densely packed, highly motile, and proliferative tissues, biophysical forces impose mechanical constraints that influence cell signaling, proliferation, and fate. These forces lead to mechanotransduction, the process by which cells convert mechanical stimuli into biochemical signals. In immune cells, traction forces generated by the cytoskeleton and motor proteins, together with integrin-mediated mechanosensing, drive various cellular processes, including antigen detection, immune synapse formation, signaling, and antigen internalization. Substrate stiffness further modulates these processes and influences proliferation and antibody responses. Beyond individual cells, these forces contribute to larger-scale mechanical stresses in tissues. For instance, in rapidly growing tumours or highly proliferative regions (such as germinal centres), high cell density and necrotic core formation enhance internal pressure, limit nutrient availability, and impose forces on neighboring cells. Such mechanical constraints influence the growth dynamics of these highly proliferative systems. Computational modelling can clarify how cells and tissues respond to mechanical cues. However, capturing driving forces remains challenging due to the complex, nonlinear, and multiscale nature of biological systems and the dynamic feedback between mechanical and biochemical processes. To address these challenges and enable realistic simulations, we are using Delaunay-Object-Dynamics (DOD), a geometric framework where cells are modelled as viscoelastic, adhesive spheres interacting in continuous 3D space. Unlike classical molecular dynamics, Delaunay-Object-Dynamics (DOD) provides a natural representation of cell surfaces via Voronoi tessellation. This allows for explicit, quantitative simulations of Newtonian forces at well-defined contact interfaces, making it particularly well-suited for densely packed tissues. By modelling these processes, our simulations allow quantitative exploration of how physical forces influence signaling-dependent decision-making, particularly by regulating key immune processes such as antibody production, which could be an important factor in effective vaccine design.

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