活体神经内分泌细胞衍射受限三维单分泌囊泡跟踪的定量分析

D.D. Li, T. Liang, A. Qu
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引用次数: 0

摘要

神经内分泌细胞通过调节分泌囊泡的胞外分泌来释放激素和递质。在整个活细胞中对单个分泌囊泡进行三维(3D)跟踪对于理解分泌囊泡的细胞内运输至关重要。但是,三维粒子跟踪的一个值得注意的问题是,横向和轴向分辨率不等同于三维活细胞图像,这是由于显微镜固有的衍射极限。衍射受限图像对粒子跟踪性能的影响尚不清楚。本文采用质心和高斯拟合跟踪算法监测单个荧光粒子的亚像素位置,表明三维单粒子跟踪的性能是非各向同性的。颗粒在轴向的跟踪效果远低于横向的跟踪效果。高斯拟合跟踪算法在轴向低信噪比在10左右或以下时提供更好的性能。利用神经内分泌细胞系PC12,我们证明了高斯拟合算法在所有三个维度上跟踪单个分泌囊泡移动的可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Quantitative analysis of diffraction-limited three-dimensional single secretory vesicle tracking in live neuroendocrine cells
Neuroendocrine cells release hormones and transmitters by regulated exocytosis of secretory vesicles. Three-dimensional (3D) tracking of single secretory vesicles throughout live whole cells is crucial for understanding the intracellular trafficking of secretory vesicles. But one notable problem with 3D particle tracking is that the lateral and axial resolution is not equivalent for 3D live-cell images, which is attributed to the diffraction limit inherent to the microscope. How the performance of particle tracking is affected by diffraction-limited images is still unclear. Here we show, employing both centroid and Gaussian-fit tracking algorithm to monitor sub-pixel positions of single fluorescent particles, that the performance of three-dimensional single particle tracking is nonisotropic. The efficacy of the particle tracking in the axial direction is much lower than that in the lateral direction. Gaussian-fit tracking algorithm provides better performance in the axial direction at low signal-to-noise levels around or below 10. Using neuroendocrine cell line PC12, we illustrate the feasibility of Gaussian-fit algorithm to follow the mobility of single secretory vesicles in all three dimensions.
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