Protocol for the detection of large dense-core vesicle exocytosis using an automated image-processing algorithm
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.<sup>1</sup>.
Authors
- Abhimanyu Dubey
- Aishwarya A. Makam
- Nikhil R. Gandasi (ORCID: https://orcid.org/0000-0001-9400-6494)
- Vishnu Ramadas
- Anly Tollan
- Ishan Bhattacharyya
Institutions
- Uppsala University (SE)
- Indian Institute of Science Bangalore (IN)
Publication Details
- Journal
- STAR Protocols
- Published
- 2025-12-01
- DOI
- https://doi.org/10.1016/j.xpro.2025.104264
- Primary Topic
- Cellular transport and secretion
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Indian Institute of Science
- Department of Biotechnology, Ministry of Science and Technology, India
- Department of Science and Technology, Ministry of Science and Technology, India
- Indian Council of Medical Research
- Novo Nordisk
- Rajiv Gandhi University of Health Sciences
- Science and Engineering Research Board