活细胞中微管长度调节的最小机制

Anna C Nelson, Melissa Rolls, Maria-Veronica Ciocanel, Scott A McKinley
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引用次数: 0

摘要

微管细胞骨架负责神经元中mrna和蛋白质的持续、长距离的细胞内转运。神经元微管必须足够稳定,以确保可靠的运输,但它们也承受着动力不稳定性,因为它们的正负端不断地在生长和收缩之间切换。这个过程允许细胞骨架的持续重建和损伤环境下的灵活性。基于\textit{果蝇}神经元微管行为的\textit{体内}实验数据,我们提出了树突微管动力学的空间显式数学模型。我们发现实验参数可以预测无界微管生长。因此,我们使用随机建模框架研究了微管生长的两个最小长度限制因素(由于资源约束的限制和由于大长度不稳定性的限制)。说明用常微分方程模型对平均场模型进行稳态分析有助于随机模型的参数化。该框架能够研究定性不同的参数制度,并为可观察和不可观察的生物测量提供预测,例如微管蛋白分配和微管蛋白光转换测量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Minimal Mechanisms of Microtubule Length Regulation in Living Cells
The microtubule cytoskeleton is responsible for sustained, long-range intracellular transport of mRNAs and proteins in neurons. Neuronal microtubules must be stable enough to ensure reliable transport, but they also undergo dynamic instability, as their plus and minus ends continuously switch between growth and shrinking. This process allows for continuous rebuilding of the cytoskeleton and for flexibility in injury settings. Motivated by \textit{in vivo} experimental data on microtubule behavior in \textit{Drosophila} neurons, we propose a spatially-explicit mathematical model of dendritic microtubule dynamics. We find that experimental parameters predict unbounded microtubule growth. We therefore investigate two minimal length-limiting factors (limitation due to resource constraints and limitation due to large length instability) for microtubule growth using a stochastic modeling framework. We show that steady-state analysis of a mean-field model using ordinary differential equations model aids in parameterizing the stochastic model. This framework enables investigation of qualitatively different parameter regimes and provides predictions for both observable and unobservable biological measurements, such as tubulin allocation and tubulin photoconversion measurements.
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