Spatially Constrained Monte Carlo Permutation Test Reveals Diffusion Changes Near Stress Granules

Abstract

Intracellular diffusion is inherently heterogeneous, yet single-particle tracking (SPT) analyses are often summarized using cell-wide average parameters that can obscure localized effects. Here, we tracked 40-nm genetically encoded multimeric (GEM) nanoparticles during stress granule (SG) formation and developed SPaCe-MC (Spatially Constrained Monte Carlo permutation test), a statistical framework that generates cytoplasm-specific null models to test whether diffusion associated with a specific cellular structure differs from that expected in the surrounding heterogeneous cytoplasm. Across three SG-inducing conditions, including oxidative stress, DDX3 inhibition, and combined treatment, bulk cytoplasmic analyses revealed distinct responses ranging from increased nanoparticle mobility to increased subdiffusive behavior. In contrast, SPaCe-MC consistently detected a local diffusion constraint in SG-associated regions relative to their treatment-matched cytoplasmic background, revealing a conserved local diffusion effect despite divergent global cytoplasmic responses. Together, our findings establish SPaCe-MC as a framework for identifying compartment-specific diffusion changes in heterogeneous cellular environments.