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<p>Anomalous, non-Gaussian diffusion is ubiquitous in living cells, but whether this statistical signature arises from static structural disorder or active cytoskeletal fluctuations remains unresolved. To decouple these factors, we used high-resolution single-particle tracking to characterize intracellular diffusion, while systematically perturbing cytoplasmic molecular crowding or cytoskeletal integrity. Our results demonstrate that the non-Gaussian, Laplace-like form of the displacement distribution is robust to cytoskeletal disruption but highly sensitive to molecular crowding. Notably, the characteristic confinement length scale, <i>ξ</i>, is significantly reduced by both increased crowding and the suppression of active fluctuations. This decoupling supports our proposed model of “active heterogeneous confinement”, where a static landscape defined by crowding is dynamically rescaled by activity. Our framework establishes diffusion statistics as a quantitative probe of the cell’s underlying biophysical state.</p>

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Statistical signatures of intracellular diffusion: Interpreting crowding and activity through non-Gaussian distributions

  • 期刊论文

  • 发表日期：

    2026年3月25日

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  • Lan Yang,
  • Ming-Li Zhang,
  • Jian Liu,
  • Liang Luo,
  • Maoxin Liu,
  • Xu Zheng,
  • Xiaosong Chen,
  • Hui Li

摘要

Anomalous, non-Gaussian diffusion is ubiquitous in living cells, but whether this statistical signature arises from static structural disorder or active cytoskeletal fluctuations remains unresolved. To decouple these factors, we used high-resolution single-particle tracking to characterize intracellular diffusion, while systematically perturbing cytoplasmic molecular crowding or cytoskeletal integrity. Our results demonstrate that the non-Gaussian, Laplace-like form of the displacement distribution is robust to cytoskeletal disruption but highly sensitive to molecular crowding. Notably, the characteristic confinement length scale, ξ, is significantly reduced by both increased crowding and the suppression of active fluctuations. This decoupling supports our proposed model of “active heterogeneous confinement”, where a static landscape defined by crowding is dynamically rescaled by activity. Our framework establishes diffusion statistics as a quantitative probe of the cell’s underlying biophysical state.