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Computational approaches for delineating lysosomes and related intracellular trafficking vesicles in confocal and other fluorescence datasets

Computational approaches for delineating lysosomes and related intracellular trafficking vesicles in confocal and other fluorescence datasets
Computational approaches for delineating lysosomes and related intracellular trafficking vesicles in confocal and other fluorescence datasets
Fluorescence datasets from investigations into intracellular trafficking compartments produce images of variable quality, scales and complexities. Investigators are therefore confronted with a choice of how to analyse this information. Here, we have used confocal immunofluorescence images of lysosomes from retinal pigment epithelial cells as an exemplar dataset, and employed three freely accessible computational approaches (Fiji, CellProfiler and Icy) to showcase their workings. A step-by-step workflow for each pipeline is described with non-specialist users in mind. These produce results including lysosomal number and shape, but also 3D outputs such as volume. Features of the three methods alongside their advantages and limitations are subsequently summarised. An important consideration, however, is that results generated from the different approaches are not necessarily comparable. Hence, users should adopt only a single method to analyse their dataset which best suit their specific requirements.
3D imaging, computation, volume, confocal microscopy, lysosome, trafficking vesicles, 3D imaging, computation, volume, confocaretinal pigment epithelium (RPE), stem cells, data integrity
1064-3745
Springer New York, NY
Ellis, Charles
507f9816-974d-4cb7-9053-91ed67cd51b8
Chatelet, David S.
62e830df-81a7-489f-82e5-0576ccb99e18
Ratnayaka, J. Arjuna
002499b8-1a9f-45b6-9539-5ac145799dfd
Ellis, Charles
507f9816-974d-4cb7-9053-91ed67cd51b8
Chatelet, David S.
62e830df-81a7-489f-82e5-0576ccb99e18
Ratnayaka, J. Arjuna
002499b8-1a9f-45b6-9539-5ac145799dfd

Ellis, Charles, Chatelet, David S. and Ratnayaka, J. Arjuna (2025) Computational approaches for delineating lysosomes and related intracellular trafficking vesicles in confocal and other fluorescence datasets (Methods in Molecular Biology), Springer New York, NY, 19pp.

Record type: Book

Abstract

Fluorescence datasets from investigations into intracellular trafficking compartments produce images of variable quality, scales and complexities. Investigators are therefore confronted with a choice of how to analyse this information. Here, we have used confocal immunofluorescence images of lysosomes from retinal pigment epithelial cells as an exemplar dataset, and employed three freely accessible computational approaches (Fiji, CellProfiler and Icy) to showcase their workings. A step-by-step workflow for each pipeline is described with non-specialist users in mind. These produce results including lysosomal number and shape, but also 3D outputs such as volume. Features of the three methods alongside their advantages and limitations are subsequently summarised. An important consideration, however, is that results generated from the different approaches are not necessarily comparable. Hence, users should adopt only a single method to analyse their dataset which best suit their specific requirements.

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Ratnayaka et al_Methods Chapter - Accepted Manuscript
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e-pub ahead of print date: 22 July 2025
Published date: 22 July 2025
Keywords: 3D imaging, computation, volume, confocal microscopy, lysosome, trafficking vesicles, 3D imaging, computation, volume, confocaretinal pigment epithelium (RPE), stem cells, data integrity

Identifiers

Local EPrints ID: 504616
URI: http://eprints.soton.ac.uk/id/eprint/504616
ISSN: 1064-3745
PURE UUID: 3f66464b-5278-4fb4-9395-d18fa5863095
ORCID for J. Arjuna Ratnayaka: ORCID iD orcid.org/0000-0002-1027-6938

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Date deposited: 16 Sep 2025 16:50
Last modified: 17 Sep 2025 01:49

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Contributors

Author: Charles Ellis
Author: David S. Chatelet

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