基于肌动蛋白的运动和整合-放电神经元的布朗棘轮模型的随机分析

H. Qian
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引用次数: 6

摘要

在最近对体外单核增生李斯特菌运动的单粒子跟踪(SPT)测量中,对细菌运动的基于肌动蛋白的随机动力学进行了统计分析(Kuo和McGrath, 2000)。非趋势轨迹的均方位移(MSD)表现为线性行为;有人提出,对布朗棘轮模型(Peskin, Odell, & Oster, 1993)的相应分析导致非单调MSD。当布朗棘轮的运动受到细菌运动的限制时,提出并随机分析了布朗棘轮的简化版本。给出了简单模型的分析结果,并对统计数据进行了分析。随机细菌运动的MSD是一个二次函数,而非趋势轨迹的MSD是线性的。通过MSD分析,得到了被推进细菌在长时间极限下的平均速度和有效扩散常数,以及短时间弛豫。当有较大的细菌阻力时,肌动蛋白与细菌之间间隙的MSD表现出振荡行为。基于肌动蛋白的运动的随机模型在数学上也等同于整合-发射神经元的模型。因此,我们的数学结果在其他生物学问题上也有应用。为了比较,本文还研究了一种分析简单的连续型BR模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Stochastic Analysis of a Brownian Ratchet Model for Actin-Based Motility and Integrate-and-Firing Neurons
In recent single-particle tracking (SPT) measurements on {\it Listeria monocytogenes} motility {\em in vitro}, the actin-based stochastic dynamics of the bacterium movement is analyzed statistically (Kuo and McGrath, 2000). The mean-square displacement (MSD) of the detrended trajectory exhibit a linear behavior; it has been suggested that a corresponding analysis for the Brownian ratchet model (Peskin, Odell, & Oster, 1993) leads to a non-monotonic MSD. A simplified version of the Brownian ratchet, when its motion is limited by the bacterium movement, is proposed and analyzed stochastically. Analytical results for the simple model are obtained and statistical data analysis is investigated. The MSD of the stochastic bacterium movement is a quadratic function while the MSD for the detrended trajectory is shown to be linear. The mean velocity and effective diffusion constant of the propelled bacterium in the long-time limit, and the short-time relaxation are obtained from the MSD analysis. The MSD of the gap between actin and the bacterium exhibits an oscillatory behavior when there is a large resistant force from the bacterium. The stochastic model for actin-based motility is also mathematically equivalent to a model for integrate-and-firing neurons. Hence our mathematical results have applications in other biological problems. For comparison, a continuous formalism of the BR model with great analytical simplicity is also studied.
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