# Protocol for the detection of large dense-core vesicle exocytosis using an automated image-processing algorithm

## TL;DR

This paper introduces a protocol using an automated image-processing algorithm to detect and analyze exocytosis in human pancreatic islet cells.

## Contribution

A novel protocol for detecting large dense-core vesicle exocytosis using Lagrangian particle tracking in high-throughput microscopy.

## Key findings

- The protocol is validated using mathematical models, TetraSpeck beads, and cell images.
- It enables efficient analysis of vesicle dynamics in human pancreatic islet cells.
- The method is applicable to other cellular processes and large datasets.

## Abstract

Investigating exocytosis in human pancreatic islet cells is challenging due to small vesicle size and variable imaging parameters. Here, we present a protocol to detect and analyze exocytosis with an image-processing algorithm using Lagrangian particle tracking. We describe steps for sample preparation, total internal reflection fluorescence (TIRF) microscopy imaging, and computational analysis. The algorithm is validated by mathematical models, TetraSpeck beads, and cell images. Its applicability to other cellular processes and its handling of large sets of data make it useful for high-throughput microscopy research.

For complete details on the use and execution of this protocol, please refer to Makam et al.1

•Instructions for isolation, culture, and transfection of human pancreatic islet cells•Steps for preparation of beads and artificial images for algorithm validation•Guidance on TIRF imaging of exocytosis events in human pancreatic islet cells•Procedure for detecting and analyzing vesicle dynamics using Lagrangian tracking

Instructions for isolation, culture, and transfection of human pancreatic islet cells

Steps for preparation of beads and artificial images for algorithm validation

Guidance on TIRF imaging of exocytosis events in human pancreatic islet cells

Procedure for detecting and analyzing vesicle dynamics using Lagrangian tracking

Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

Investigating exocytosis in human pancreatic islet cells is challenging due to small vesicle size and variable imaging parameters. Here, we present a protocol to detect and analyze exocytosis with an image-processing algorithm using Lagrangian particle tracking. We describe steps for sample preparation, total internal reflection fluorescence (TIRF) microscopy imaging, and computational analysis. The algorithm is validated by mathematical models, TetraSpeck beads, and cell images. Its applicability to other cellular processes and its handling of large sets of data make it useful for high-throughput microscopy research.