Chou Vivian T, Yesilyurt Hunkar Gizem, Lai Hoyin, Long Jennifer B, Arnes Mercedes, Obbad Kamal, Jones Michael, Sasaki Hideki, Lucas Luciano A G, Alworth Sam, Lee James Shih-Jong, Van Vactor David
Blavatnik Institute of Cell Biology and Program in Neuroscience, Harvard Medical School.
DRVision Technologies LLC.
J Vis Exp. 2020 May 12(159). doi: 10.3791/61159.
Microtubules (MTs) play critical roles in neuronal development, but many questions remain about the molecular mechanisms of their regulation and function. Furthermore, despite progress in understanding postsynaptic MTs, much less is known about the contributions of presynaptic MTs to neuronal morphogenesis. In particular, studies of in vivo MT dynamics in Drosophila sensory dendrites yielded significant insights into polymer-level behavior. However, the technical and analytical challenges associated with live imaging of the fly neuromuscular junction (NMJ) have limited comparable studies of presynaptic MT dynamics. Moreover, while there are many highly effective software strategies for automated analysis of MT dynamics in vitro and ex vivo, in vivo data often necessitate significant operator input or entirely manual analysis due to inherently inferior signal-to-noise ratio in images and complex cellular morphology. To address this, this study optimized a new software platform for automated and unbiased in vivo particle detection. Multiparametric analysis of live time-lapse confocal images of EB1-GFP labeled MTs was performed in both dendrites and the NMJ of Drosophila larvae and found striking differences in MT behaviors. MT dynamics were furthermore analyzed following knockdown of the MT-associated protein (MAP) dTACC, a key regulator of Drosophila synapse development, and identified statistically significant changes in MT dynamics compared to wild type. These results demonstrate that this novel strategy for the automated multiparametric analysis of both pre- and postsynaptic MT dynamics at the polymer-level significantly reduces human-in-the-loop criteria. The study furthermore shows the utility of this method in detecting distinct MT behaviors upon dTACC-knockdown, indicating a possible future application for functional screens of factors that regulate MT dynamics in vivo. Future applications of this method may also focus on elucidating cell type and/or compartment-specific MT behaviors, and multicolor correlative imaging of EB1-GFP with other cellular and subcellular markers of interest.
微管（MTs）在神经元发育中起着关键作用，但关于其调节和功能的分子机制仍存在许多问题。此外，尽管在理解突触后微管方面取得了进展，但对于突触前微管对神经元形态发生的贡献了解甚少。特别是，对果蝇感觉树突中体内微管动力学的研究为聚合物水平的行为提供了重要见解。然而，与果蝇神经肌肉接头（NMJ）的实时成像相关的技术和分析挑战限制了对突触前微管动力学的类似研究。此外，虽然有许多高效的软件策略用于体外和离体微管动力学的自动分析，但由于图像中固有的低信噪比和复杂的细胞形态，体内数据通常需要大量的操作员输入或完全手动分析。为了解决这个问题，本研究优化了一个用于自动和无偏体内粒子检测的新软件平台。在果蝇幼虫的树突和神经肌肉接头中对EB1-GFP标记的微管的实时延时共聚焦图像进行了多参数分析，发现微管行为存在显著差异。此外，在敲低微管相关蛋白（MAP）dTACC（果蝇突触发育的关键调节因子）后分析了微管动力学，并确定与野生型相比微管动力学有统计学上的显著变化。这些结果表明，这种用于聚合物水平突触前和突触后微管动力学自动多参数分析的新策略显著降低了人为干预标准。该研究还表明了该方法在检测dTACC敲低后不同微管行为方面的实用性，表明该方法在体内调节微管动力学的因子功能筛选中可能有未来应用。该方法的未来应用还可能集中在阐明细胞类型和/或特定区域的微管行为，以及EB1-GFP与其他感兴趣的细胞和亚细胞标记物的多色相关成像。
