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Abstract

Biology

Automated Detection and Analysis of Exocytosis

Published: September 11th, 2021

DOI:

10.3791/62400

1UNC Neuroscience Center, Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill

ERRATUM NOTICE

Important: There has been an erratum issued for this article. Read more …

Timelapse TIRF microscopy of pH-sensitive GFP (pHluorin) attached to vesicle SNARE proteins is an effective method to visualize single vesicle exocytic events in cell culture. To perform an unbiased, efficient identification and analysis of such events, a computer-vision based approach was developed and implemented in MATLAB. The analysis pipeline consists of a cell segmentation and exocytic-event identification algorithm. The computer-vision approach includes tools for investigating multiple parameters of single events, including the half-life of fluorescence decay and peak ΔF/F, as well as whole-cell analysis of the frequency of exocytosis. These and other parameters of fusion are used in a classification approach to distinguish distinct fusion modes. Here a newly built GUI performs the analysis pipeline from start to finish. Further adaptation of Ripley's K function in R Studio is used to distinguish between clustered, dispersed, or random occurrence of fusion events in both space and time.

Erratum

Retraction: Automated Detection and Analysis of Exocytosis

The article Automated Detection and Analysis of Exocytosis has been retracted by the journal due to concerns regarding the validity of the presented data.

Tags

Keywords Exocytosis

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