Non-Markovian Persistent Random Walk Model for Intracellular Transport

Nickolay Korabel, Hamed Al Shamsi, Mykola Korabel, Alexey Ivanov, Sergei Fedotov

Research output: Contribution to journalArticlepeer-review

4 Downloads (Pure)

Abstract

Transport of vesicles and organelles inside cells consists of constant-speed bidirectional movement along cytoskeletal filaments interspersed by periods of idling. This transport shows many features of anomalous diffusion. In this paper, we develop a non-Markovian persistent random walk model for intracellular transport that incorporates the removal rate of organelles. The model consists of two active states with different speeds and one resting state. The organelle transitions between states with switching rates that depend on the residence time the organelle spends in each state. The mesoscopic master equations that describe the average densities of intracellular transport in each of the three states are the main results of the paper. We also derive ordinary differential equations for the dynamics for the first and second moments of the organelles’ position along the cell. Furthermore, we analyse models with power-law distributed random times, which reveal the prevalence of the Mittag-Leffler resting state and its contribution to subdiffusive and superdiffusive behaviour. Finally, we demonstrate a non-Markovian non-additivity effect when the switching rates
and transport characteristics depend on the rate of organelles removal. The analytical calculations are in good agreement with numerical Monte Carlo simulations. Our results shed light on the dynamics of intracellular transport and emphasise the effects of rest times on the persistence of random walks
in complex biological systems.
Original languageEnglish
Number of pages17
JournalFractal and Fractional
Volume7
Issue number758
Publication statusPublished - 15 Oct 2023

Fingerprint

Dive into the research topics of 'Non-Markovian Persistent Random Walk Model for Intracellular Transport'. Together they form a unique fingerprint.

Cite this