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Time-lapse confocal imaging datasets to assess structural and dynamic properties of subcellular nanostructures
Time-lapse optical microscopy datasets from living cells can potentially afford an enormous amount of quantitative information on the relevant structural and dynamic properties of sub-cellular organelles/structures, provided that both the spatial and temporal dimensions are properly sampled during t...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6142892/ https://www.ncbi.nlm.nih.gov/pubmed/30226484 http://dx.doi.org/10.1038/sdata.2018.191 |
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author | Ferri, Gianmarco Digiacomo, Luca D’Autilia, Francesca Durso, William Caracciolo, Giulio Cardarelli, Francesco |
author_facet | Ferri, Gianmarco Digiacomo, Luca D’Autilia, Francesca Durso, William Caracciolo, Giulio Cardarelli, Francesco |
author_sort | Ferri, Gianmarco |
collection | PubMed |
description | Time-lapse optical microscopy datasets from living cells can potentially afford an enormous amount of quantitative information on the relevant structural and dynamic properties of sub-cellular organelles/structures, provided that both the spatial and temporal dimensions are properly sampled during the experiment. Here we provide exemplary live-cell, time-lapse confocal imaging datasets corresponding to three sub-cellular structures of the endo-lysosomal pathway, i.e. early endosomes, late endosomes and lysosomes, along with detailed guidelines to produce analogous experiments. Validation of the datasets is conducted by means of established analytical tools to extract the structural and dynamic properties at the sub-cellular scale, such as Single Particle Tracking (SPT) and imaging derived Mean Square Displacement (iMSD) analyses. In our aim, the present work would help other researchers in the field to reuse the provided datasets for their own scopes, and to combine their creative approaches/analyses to similar acquisitions. |
format | Online Article Text |
id | pubmed-6142892 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-61428922018-09-28 Time-lapse confocal imaging datasets to assess structural and dynamic properties of subcellular nanostructures Ferri, Gianmarco Digiacomo, Luca D’Autilia, Francesca Durso, William Caracciolo, Giulio Cardarelli, Francesco Sci Data Data Descriptor Time-lapse optical microscopy datasets from living cells can potentially afford an enormous amount of quantitative information on the relevant structural and dynamic properties of sub-cellular organelles/structures, provided that both the spatial and temporal dimensions are properly sampled during the experiment. Here we provide exemplary live-cell, time-lapse confocal imaging datasets corresponding to three sub-cellular structures of the endo-lysosomal pathway, i.e. early endosomes, late endosomes and lysosomes, along with detailed guidelines to produce analogous experiments. Validation of the datasets is conducted by means of established analytical tools to extract the structural and dynamic properties at the sub-cellular scale, such as Single Particle Tracking (SPT) and imaging derived Mean Square Displacement (iMSD) analyses. In our aim, the present work would help other researchers in the field to reuse the provided datasets for their own scopes, and to combine their creative approaches/analyses to similar acquisitions. Nature Publishing Group 2018-09-18 /pmc/articles/PMC6142892/ /pubmed/30226484 http://dx.doi.org/10.1038/sdata.2018.191 Text en Copyright © 2018, The Author(s) http://creativecommons.org/licenses/by/4.0/ Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files made available in this article. |
spellingShingle | Data Descriptor Ferri, Gianmarco Digiacomo, Luca D’Autilia, Francesca Durso, William Caracciolo, Giulio Cardarelli, Francesco Time-lapse confocal imaging datasets to assess structural and dynamic properties of subcellular nanostructures |
title | Time-lapse confocal imaging datasets to assess structural and dynamic properties of subcellular nanostructures |
title_full | Time-lapse confocal imaging datasets to assess structural and dynamic properties of subcellular nanostructures |
title_fullStr | Time-lapse confocal imaging datasets to assess structural and dynamic properties of subcellular nanostructures |
title_full_unstemmed | Time-lapse confocal imaging datasets to assess structural and dynamic properties of subcellular nanostructures |
title_short | Time-lapse confocal imaging datasets to assess structural and dynamic properties of subcellular nanostructures |
title_sort | time-lapse confocal imaging datasets to assess structural and dynamic properties of subcellular nanostructures |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6142892/ https://www.ncbi.nlm.nih.gov/pubmed/30226484 http://dx.doi.org/10.1038/sdata.2018.191 |
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