Diffusion approximation of the stochastic process of microtubule assembly
Diffusion approximation of the stochastic process of microtubule assembly
复制标题
DOI：
10.1006/bulm.2001.0265
复制
发表时间：
2002-03-01
影响因子：
3.5
通讯作者：
Maly, IV
中科院分区：
文献类型：
--
作者：
Maly, IV
微管是引导细胞内运动的蛋白质聚合物。动态不稳定性 (DI) 模型详细描述了微管在伸长、缩短和暂停状态之间的随机切换。最近，我们在现象学上将微管的动力学描述为其末端的广义扩散。这项工作研究了扩散动力学的起源和扩散模型的准确性。结果表明，经历 DI 的微管末端的漂移渐近地接近维纳扩散过程。通过将其预测与 DI 模拟结果进行比较来评估扩散近似的准确性。两种模型预测的微管长度和寿命的稳态分布在所考虑的两种细胞类型之间存在质的差异。然而，扩散模型的预测在每种情况下实际上与 DI 模型的预测相同，也与实验数据一致。因此，微管组装的独特随机过程在细胞尺度上收敛为一种自然界中广泛存在的扩散过程。这一结果被认为是生物组织从分子水平向细胞水平转变过程中动力学性质发生质变的一个例子。此外，它还建议采用扩散过程理论来研究细胞中微管的功能。 (C) 2002 年数学生物学学会。
Microtubules are protein polymers that guide intracellular motility. Stochastic switching of a microtubule between states of elongation, shortening, and pause is described in detail by the dynamic instability (DI) model. Recently we have described the dynamics of microtubules phenomenologically as generalized diffusion of their ends. Genesis of the diffusion dynamics and accuracy of diffusion model are studied in this work. It is shown that wandering of the end of a microtubule undergoing DI asymptotically approaches the Wiener diffusion process. Accuracy of the diffusion approximation is evaluated by comparing its predictions with results of simulation of DI. Stationary distributions of microtubule length and life-time that are predicted by both models differ qualitatively between two cell types considered. However, predictions of the diffusion model are in each case practically identical to predictions of the DI model being also consistent with experimental data. The peculiar stochastic process of microtubule assembly thus converges at cell scale to a kind of widespread-in-nature diffusion process. This result is considered an example of qualitative change in dynamical properties in transition from the molecular to cellular level of biological organization. Additionally, it suggests employment of diffusion process theory in studying functions of microtubules in the cell. (C) 2002 Society for Mathematical Biology.