We present a framework for generating whole-cell digital twin simulations which integrates 4D (x,y,z,t) lattice light-sheet microscopy (LLSM) data with particle-based reaction-diffusion modeling to capture intracellular organelle dynamics. Using experimental imaging data from Cal27 cells, we construct spatially resolved digital twins that incorporate mitochondrial networks, microtubule networks, dynein and kinesin motors, the plasma membrane, and the nucleus. Passive diffusive mitochondrial dynamics are parameterized using stochastic reaction-diffusion simulations in ReaDDy, while active transport is modeled by explicitly incorporating motor-driven transport along a diffusing, polarized microtubule network. Our simulations accurately reproduce experimentally observed trends in mitochondrial motility and network remodeling across three pharmacological perturbation conditions: untreated control cells with intact microtubules, cells treated with nocodazole for 30 minutes leading to partial microtubule depolymerization, and cells treated for 60 minutes resulting in near-complete microtubule disruption. Demonstrating predictive capability without explicit parameterization for such intermediate perturbations, our approach provides a robust platform for studying intracellular dynamics and mechanistic perturbations in a biologically grounded manner. This digital twin framework offers new avenues for modeling subcellular processes and investigating the effects of cytoskeletal disruptions on mitochondrial network dynamics.
Arkfeld et al. (Sun,) studied this question.