Kuznetsov Ivan A, Kuznetsov Andrey V
Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, USA.
Dept. of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC 27695-7910, USA.
J Theor Biol. 2022 Aug 7;546:111161. doi: 10.1016/j.jtbi.2022.111161. Epub 2022 May 13.
Even though most axonal cargos are synthesized in the soma, the concentration of many of these cargos is larger at the presynaptic terminal than in the soma. This requires transport of these cargos from the soma to the presynaptic terminal or other active sites in the axon. Axons utilize both bidirectional (for example, slow axonal transport) and unidirectional (for example, fast anterograde axonal transport) modes of cargo transport. Bidirectional transport seems to be less efficient because it requires more time and takes more energy to deliver cargos. In this paper, we studied a family of models which differ by the modes of axonal cargo transport (such as anterograde and retrograde motor-driven transport and passive diffusion) as well as by the presence or absence of pausing states. The models are studied to investigate their ability to describe axonal transport against the cargo concentration gradient. We argue that bidirectional axonal transport is described by a higher-order mathematical model, which allows imposing cargo concentration not only at the axon hillock but also at the axon terminal. The unidirectional transport model allows only for the imposition of cargo concentration at the axon hillock. Due to the great lengths of the axons, anterograde transport mostly relies on molecular motors, such as kinesins, to deliver cargos synthesized in the soma to the terminal and other active sites in the axon. Retrograde transport can be also motor-driven, in which case cargos are transported by dynein motors. If cargo concentration at the axon tip is higher than at the axon hillock, retrograde transport can also occur by cargo diffusion. However, because many axonal cargos are large or they assemble in multiprotein complexes for axonal transport, the diffusivity of such cargos is very small. We investigated the case of a small cargo diffusivity using a perturbation technique and found that for this case the effect of diffusion is limited to a very thin diffusion boundary layer near the axon tip. If cargo diffusivity is decreased in the model, we show that without motor-driven retrograde transport the model is unable to describe a high cargo concentration at the axon tip. To the best of our knowledge, our paper presents the first explanation for the utilization of seemingly inefficient bidirectional transport in neurons.
尽管大多数轴突货物是在胞体中合成的，但这些货物中的许多在突触前末端的浓度比在胞体中更高。这就需要将这些货物从胞体运输到突触前末端或轴突中的其他活跃位点。轴突利用双向（例如，慢速轴突运输）和单向（例如，快速顺行轴突运输）两种货物运输模式。双向运输似乎效率较低，因为它需要更多时间且消耗更多能量来运送货物。在本文中，我们研究了一系列模型，这些模型因轴突货物运输模式（如顺行和逆行马达驱动运输以及被动扩散）以及是否存在暂停状态而有所不同。研究这些模型是为了考察它们描述逆着货物浓度梯度的轴突运输的能力。我们认为双向轴突运输由一个高阶数学模型描述，该模型不仅允许在轴突丘处施加货物浓度，还允许在轴突末端施加货物浓度。单向运输模型仅允许在轴突丘处施加货物浓度。由于轴突长度很长，顺行运输主要依赖分子马达，如驱动蛋白，将在胞体中合成的货物运送到轴突末端和轴突中的其他活跃位点。逆行运输也可以由马达驱动，在这种情况下，货物由动力蛋白马达运输。如果轴突末端的货物浓度高于轴突丘处的货物浓度，逆行运输也可以通过货物扩散发生。然而，由于许多轴突货物很大，或者它们组装成多蛋白复合物进行轴突运输，这些货物的扩散系数非常小。我们使用微扰技术研究了货物扩散系数小的情况，发现对于这种情况，扩散的影响仅限于轴突末端附近非常薄的扩散边界层。如果在模型中降低货物扩散系数，我们表明在没有马达驱动的逆行运输的情况下，该模型无法描述轴突末端的高货物浓度。据我们所知，我们的论文首次解释了神经元中看似低效的双向运输的用途。
