Automated Detection and Analysis of Exocytosis

Fabio Urbina; Stephanie L. Gupton

doi:10.3791/62400

Detección y análisis automatizados de exocitosis

JoVE Journal
Biology
Author Produced

A subscription to JoVE is required to view this content. Sign in or start your free trial.

JoVE Journal Biology

Automated Detection and Analysis of Exocytosis

Detección y análisis automatizados de exocitosis

Full Text

3,999 Views

13:28 min

September 11, 2021

DOI: 10.3791/62400-v

Fabio Urbina¹, Stephanie L. Gupton¹

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

Please note that some of the translations on this page are AI generated. Click here for the English version.

Overview

This study presents a novel automated computer vision software designed for the detection and analysis of exocytic events utilizing pH-sensitive fluorescent probes. The software, compatible with RStudio, aids researchers in identifying fusion events and analyzing their spatiotemporal parameters.

Key Study Components

Research Area

Cell biology
Exocytosis
Fluorescent imaging

Background

Understanding exocytosis is crucial for elucidating cellular communication.
Current methods for analyzing exocytosis are often manual and time-consuming.
This research addresses the need for automated solutions in studying exocytic events.

Methods Used

Automated detection of exocytosis events using computer vision.
Application of RStudio for data analysis.
Classification of events into distinct fusion modes based on previously described literature.

Main Results

Successful detection of exocytosis events marked by pH-sensitive fluorophores.
Output features include spatial distribution, frequency, and individual properties of exocytic events.
Classification of events into four distinct modes based on probabilistic thresholds.

Conclusions

The automated software significantly enhances the analysis of exocytosis.
This tool facilitates high-throughput studies of cellular processes.

Frequently Asked Questions

What are the key features of the automated software?

The software automatically detects exocytic events, analyzes their spatial distribution and frequency, and classifies them into four distinct modes.

How does the software improve upon current methods?

It streamlines the detection and analysis process, reducing manual effort and increasing efficiency.

What types of imaging are compatible with the software?

The software works with Total Internal Reflection Fluorescence (TIRF) imaging of pH-sensitive fluorophores.

Is user input required for mask files?

Yes, users can create and provide custom mask files or use the included mask maker tool.

What parameters do users need to input for analysis?

Users need to input the frame rate of images, pixel size, and the location of data and mask files.

What type of output does the software generate?

It generates analysis files containing statistics and detailed information on exocytic events.

Can the software handle large datasets?

Yes, it is designed to handle multiple data files efficiently.

Desarrollamos un software automatizado de visión por computadora para detectar eventos exocióticos marcados por sondas fluorescentes sensibles al pH. Aquí, demostramos el uso de una interfaz gráfica de usuario y RStudio para detectar eventos de fusión, analizar y mostrar parámetros espaciotemporales de fusión y clasificar eventos en distintos modos de fusión.

El software automated Detection and Analysis Of Exocytosis permitirá al usuario detectar automáticamente eventos exocíticos y secuencias de imágenes TIRF de fluoróforos sensibles al pH. También producirá automáticamente características de la exocitosis, como la distribución espacial o la frecuencia, así como propiedades individuales de eventos exocíticos, como la vida media o el cambio en la fluorescencia sobre el fondo. Además, se incluye una opción para clasificar los eventos exocióticos en cuatro modos de exocitosis, previamente descritos en la literatura.

Para utilizar el software de detección y análisis automatizado de exocitosis, primero hará clic en el botón Buscar conjunto de datos y navegará hasta donde se depositan sus datos, y querrá colocar una carpeta llamada datos sin procesar. Sus archivos de datos rellenarán automáticamente la lista aquí, y puede tener cualquier número de archivos de datos en esta carpeta. A continuación, querrá elegir un directorio para el que se depositarán sus archivos de análisis.

View the full transcript and gain access to thousands of scientific videos