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Quantitative analysis of plant ER architecture and dynamics
The endoplasmic reticulum (ER) is a highly dynamic polygonal membrane network composed of interconnected tubules and sheets (cisternae) that forms the first compartment in the secretory pathway involved in protein translocation, folding, glycosylation, quality control, lipid synthesis, calcium signa...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6395764/ https://www.ncbi.nlm.nih.gov/pubmed/30816109 http://dx.doi.org/10.1038/s41467-019-08893-9 |
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author | Pain, Charlotte Kriechbaumer, Verena Kittelmann, Maike Hawes, Chris Fricker, Mark |
author_facet | Pain, Charlotte Kriechbaumer, Verena Kittelmann, Maike Hawes, Chris Fricker, Mark |
author_sort | Pain, Charlotte |
collection | PubMed |
description | The endoplasmic reticulum (ER) is a highly dynamic polygonal membrane network composed of interconnected tubules and sheets (cisternae) that forms the first compartment in the secretory pathway involved in protein translocation, folding, glycosylation, quality control, lipid synthesis, calcium signalling, and metabolon formation. Despite its central role in this plethora of biosynthetic, metabolic and physiological processes, there is little quantitative information on ER structure, morphology or dynamics. Here we describe a software package (AnalyzER) to automatically extract ER tubules and cisternae from multi-dimensional fluorescence images of plant ER. The structure, topology, protein-localisation patterns, and dynamics are automatically quantified using spatial, intensity and graph-theoretic metrics. We validate the method against manually-traced ground-truth networks, and calibrate the sub-resolution width estimates against ER profiles identified in serial block-face SEM images. We apply the approach to quantify the effects on ER morphology of drug treatments, abiotic stress and over-expression of ER tubule-shaping and cisternal-modifying proteins. |
format | Online Article Text |
id | pubmed-6395764 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-63957642019-03-04 Quantitative analysis of plant ER architecture and dynamics Pain, Charlotte Kriechbaumer, Verena Kittelmann, Maike Hawes, Chris Fricker, Mark Nat Commun Article The endoplasmic reticulum (ER) is a highly dynamic polygonal membrane network composed of interconnected tubules and sheets (cisternae) that forms the first compartment in the secretory pathway involved in protein translocation, folding, glycosylation, quality control, lipid synthesis, calcium signalling, and metabolon formation. Despite its central role in this plethora of biosynthetic, metabolic and physiological processes, there is little quantitative information on ER structure, morphology or dynamics. Here we describe a software package (AnalyzER) to automatically extract ER tubules and cisternae from multi-dimensional fluorescence images of plant ER. The structure, topology, protein-localisation patterns, and dynamics are automatically quantified using spatial, intensity and graph-theoretic metrics. We validate the method against manually-traced ground-truth networks, and calibrate the sub-resolution width estimates against ER profiles identified in serial block-face SEM images. We apply the approach to quantify the effects on ER morphology of drug treatments, abiotic stress and over-expression of ER tubule-shaping and cisternal-modifying proteins. Nature Publishing Group UK 2019-02-28 /pmc/articles/PMC6395764/ /pubmed/30816109 http://dx.doi.org/10.1038/s41467-019-08893-9 Text en © The Author(s) 2019 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/. |
spellingShingle | Article Pain, Charlotte Kriechbaumer, Verena Kittelmann, Maike Hawes, Chris Fricker, Mark Quantitative analysis of plant ER architecture and dynamics |
title | Quantitative analysis of plant ER architecture and dynamics |
title_full | Quantitative analysis of plant ER architecture and dynamics |
title_fullStr | Quantitative analysis of plant ER architecture and dynamics |
title_full_unstemmed | Quantitative analysis of plant ER architecture and dynamics |
title_short | Quantitative analysis of plant ER architecture and dynamics |
title_sort | quantitative analysis of plant er architecture and dynamics |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6395764/ https://www.ncbi.nlm.nih.gov/pubmed/30816109 http://dx.doi.org/10.1038/s41467-019-08893-9 |
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