Lateral drift correction in time-laps images by the particle-tracking algorithm

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作者
Marko Kreft
Nina Vardjan
Matjaž Stenovec
Robert Zorec
机构
[1] University of Ljubljana,Laboratory of Neuroendocrinology
[2] Celica Biomedical Center,Molecular Cell Physiology, Faculty of Medicine, Institute of Pathophysiology
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关键词
Neuroendocrine cells; Lactotrophs; Synaptophluorin; Confocal microscopy imaging; Lateral drift;
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摘要
In long-term time-laps imaging of living cells, a significant lateral drift of the fluorescently labeled structures is often observed due to many reasons including superfusion of solution, temperature gradients, bolus addition of pharmacological agents and cell motility. We have detected lateral drift in long-term time-laps confocal imaging by tracking fluorescent puncta, which represent single exocytotic vesicles expressing synaptopHluorin (spH), a pH sensitive green fluorescence protein. Following the initial increase in fluorescence intensity due to alkalinization of vesicle lumen, the spH fluorescent puncta dimmed, which may be attributed to the resealing of the fusion pore and subsequent slow reacidification of the vesicle, or alternatively the dimming may be due to a significant lateral drift of the vesicle out of the region of interest (ROI). We identified and compensated the lateral drift by tracking particles present in the confocal images, without any additional mechanical and/or optical hardware components. The peak of the Gaussian two-dimensional (2D) curve fitted to the fluorescent particle intensity profile was recorded as the X and Y coordinates of the vesicle in each frame. The resulting coordinates of vesicle positions were averaged and rounded to the nearest pixel value, which was used to correct the drift in the time-laps images. In drift corrected time-laps images, the vesicle remained enclosed by the ROI, and the time dependent changes of spH fluorescence intensity averaged from the ROI remained at a constant level, revealing that endocytosis with subsequent slow reacidification of vesicles was an unlikely event.
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