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理论轴突损伤时的轴突运输

Axonal transport during injury on a theoretical axon.

作者信息

Chandra Soumyadeep, Chatterjee Rounak, Olmsted Zachary T, Mukherjee Amitava, Paluh Janet L

机构信息

Electrical and Computer Science Engineering, Purdue University, West Lafayette, IN, United States.

Department of Electronics, Electrical and Systems Engineering, University of Birmingham, Birmingham, United Kingdom.

出版信息

Front Cell Neurosci. 2023 Aug 11;17:1215945. doi: 10.3389/fncel.2023.1215945. eCollection 2023.

Abstract

Neurodevelopment, plasticity, and cognition are integral with functional directional transport in neuronal axons that occurs along a unique network of discontinuous polar microtubule (MT) bundles. Axonopathies are caused by brain trauma and genetic diseases that perturb or disrupt the axon MT infrastructure and, with it, the dynamic interplay of motor proteins and cargo essential for axonal maintenance and neuronal signaling. The inability to visualize and quantify normal and altered nanoscale spatio-temporal dynamic transport events prevents a full mechanistic understanding of injury, disease progression, and recovery. To address this gap, we generated DyNAMO, a Dynamic Nanoscale Axonal MT Organization model, which is a biologically realistic theoretical axon framework. We use DyNAMO to experimentally simulate multi-kinesin traffic response to focused or distributed tractable injury parameters, which are MT network perturbations affecting MT lengths and multi-MT staggering. We track kinesins with different motility and processivity, as well as their influx rates, in-transit dissociation and reassociation from inter-MT reservoirs, progression, and quantify and spatially represent motor output ratios. DyNAMO demonstrates, in detail, the complex interplay of mixed motor types, crowding, kinesin off/on dissociation and reassociation, and injury consequences of forced intermingling. Stalled forward progression with different injury states is seen as persistent dynamicity of kinesins transiting between MTs and inter-MT reservoirs. DyNAMO analysis provides novel insights and quantification of axonal injury scenarios, including local injury-affected ATP levels, as well as relates these to influences on signaling outputs, including patterns of gating, waves, and pattern switching. The DyNAMO model significantly expands the network of heuristic and mathematical analysis of neuronal functions relevant to axonopathies, diagnostics, and treatment strategies.

摘要

神经发育、可塑性和认知与神经元轴突中的功能性定向运输紧密相连,这种运输沿着由不连续的极性微管(MT)束构成的独特网络发生。轴突病由脑外伤和遗传疾病引起,这些疾病会扰乱或破坏轴突MT基础设施,进而影响运动蛋白与货物之间的动态相互作用,而这种相互作用对于轴突维持和神经元信号传导至关重要。无法可视化和量化正常及改变后的纳米级时空动态运输事件,阻碍了我们对损伤、疾病进展和恢复的全面机制理解。为了填补这一空白,我们构建了DyNAMO,即动态纳米级轴突MT组织模型,它是一个具有生物学现实意义的理论轴突框架。我们使用DyNAMO实验模拟多驱动蛋白对聚焦或分布式可控损伤参数的运输反应,这些参数是影响MT长度和多MT交错排列的MT网络扰动。我们追踪具有不同运动性和持续性的驱动蛋白,以及它们的流入速率、在MT间储库中的运输解离和重新结合、进程,并量化和空间表示运动输出比率。DyNAMO详细展示了混合运动类型、拥挤、驱动蛋白的离/上解离和重新结合以及强制混合的损伤后果之间的复杂相互作用。不同损伤状态下的停滞向前进程表现为驱动蛋白在MT和MT间储库之间过渡的持续动态性。DyNAMO分析为轴突损伤情况提供了新的见解和量化,包括局部损伤影响的ATP水平,并将这些与对信号输出的影响相关联,包括门控、波和模式切换模式。DyNAMO模型显著扩展了与轴突病、诊断和治疗策略相关的神经元功能的启发式和数学分析网络。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b5b/10450981/e07d00cf5da1/fncel-17-1215945-g0001.jpg

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