Neuroscience Institute Cavalieri Ottolenghi, University of Turin.
Neuroscience Institute Cavalieri Ottolenghi, University of Turin; Department of Neuroscience Rita Levi-Montalcini, University of Turin.
J Vis Exp. 2024 Aug 9(210). doi: 10.3791/67163.
Effective live-imaging techniques are crucial to assess neuronal morphology in order to measure neurite outgrowth in real time. The proper measurement of neurite outgrowth has been a long-standing challenge over the years in the neuroscience research field. This parameter serves as a cornerstone in numerous in vitro experimental setups, ranging from dissociated cultures and organotypic cultures to cell lines. By quantifying the neurite length, it is possible to determine if a specific treatment worked or if axonal regeneration is enhanced in different experimental groups. In this study, the aim is to demonstrate the robustness and accuracy of the Incucyte Neurotrack neurite outgrowth analysis software. This semi-automatic software is available in a time-lapse microscopy system which offers several advantages over commonly used methodologies in the quantification of the neurite length in phase contrast images. The algorithm masks and quantifies several parameters in each image and returns neuronal cell metrics, including neurite length, branch points, cell-body clusters, and cell-body cluster areas. Firstly, we validated the robustness and accuracy of the software by correlating its values with those of the manual NeuronJ, a Fiji plug-in. Secondly, we used the algorithm which is able to work both on phase contrast images as well as on immunocytochemistry images. Using specific neuronal markers, we validated the feasibility of the fluorescence-based neurite outgrowth analysis on sensory neurons in vitro cultures. Additionally, this software can measure neurite length across various seeding conditions, ranging from individual cells to complex neuronal nets. In conclusion, the software provides an innovative and time-effective platform for neurite outgrowth assays, paving the way for faster and more reliable quantifications.
有效的活体成像技术对于评估神经元形态学至关重要，以便实时测量神经突生长。多年来，神经科学研究领域一直面临着正确测量神经突生长的挑战。这个参数是许多体外实验设置的基石，包括分离培养和器官型培养以及细胞系。通过量化神经突长度，可以确定特定的处理是否有效，或者不同实验组的轴突再生是否增强。在这项研究中，目的是展示 Incucyte Neurotrack 神经突生长分析软件的稳健性和准确性。这种半自动软件可用于延时显微镜系统，与在相差对比度图像中量化神经突长度的常用方法相比，它具有多个优势。该算法在每张图像中屏蔽和量化多个参数，并返回神经元细胞指标，包括神经突长度、分支点、细胞体簇和细胞体簇面积。首先，我们通过将其值与手动 NeuronJ（一个 Fiji 插件）进行相关性验证来验证软件的稳健性和准确性。其次，我们使用了能够同时处理相差对比度图像和免疫细胞化学图像的算法。使用特定的神经元标记物，我们验证了在体外培养的感觉神经元上进行荧光基神经突生长分析的可行性。此外，该软件可以测量各种播种条件下的神经突长度，从单个细胞到复杂的神经元网络。总之，该软件为神经突生长测定提供了一个创新且高效的平台，为更快、更可靠的定量分析铺平了道路。
