Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/43311
Title: Dynein-driven self-organization of microtubules: An entropy- and network-based analysis
Authors: Frolov, Nikita
BIJNENS, Bram 
Ruiz-Reynes, Daniel
Gelens, Lendert
Issue Date: 2024
Publisher: PERGAMON-ELSEVIER SCIENCE LTD
Source: Chaos, solitons and fractals, 184 (Art N° 115053)
Abstract: Microtubules self -organize to form part of the cellular cytoskeleton. They give cells their shape and play a crucial role in cell division and intracellular transport. Strikingly, microtubules driven by motor proteins reorganize into stable mitotic/meiotic spindles with high spatial and temporal precision during successive cell division cycles. Although the topic has been extensively studied, the question remains: What defines such microtubule networks' spatial order and robustness? Here, we aim to approach this problem by analyzing a simplified computational model of radial microtubule self -organization driven by a single type of motor protein - dyneins. We establish that the spatial order of the steady-state pattern is likely associated with the dyneindriven microtubule motility. At the same time, the structure of the microtubule network is likely linked to its connectivity at the beginning of self -organization. Using the continuous variation of dynein concentration, we reveal hysteresis in microtubule self -organization, ensuring the stability of radial filament structures.
Notes: Frolov, N (corresponding author), Katholieke Univ Leuven, Dept Cellular & Mol Med, Lab Dynam Biol Syst, B-3000 Leuven, Belgium.
nikita.frolov@kuleuven.be; lendert.gelens@kuleuven.be
Keywords: Microtubule network;Entropy;Pattern formation;Agent-based modeling
Document URI: http://hdl.handle.net/1942/43311
ISSN: 0960-0779
e-ISSN: 1873-2887
DOI: 10.1016/j.chaos.2024.115053
ISI #: 001246910300001
Rights: 2024 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
Category: A1
Type: Journal Contribution
Appears in Collections:Research publications

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