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An Approach to Quantify Endomembrane Dynamics in Pollen Utilizing Bioactive Chemicals

Tip growth of pollen tubes and root hairs occurs via rapid polar growth. These rapidly elongating cells require tip-focused endomembrane trafficking for the deposition and recycling of proteins, membranes, and cell wall materials. Most of the image-based data published to date are subjective and non...

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Detalles Bibliográficos
Autores principales: Ung, Nolan, Brown, Michelle Q., Hicks, Glenn R., Raikhel, Natasha V.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Authors. 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7105205/
https://www.ncbi.nlm.nih.gov/pubmed/23118478
http://dx.doi.org/10.1093/mp/sss092
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author Ung, Nolan
Brown, Michelle Q.
Hicks, Glenn R.
Raikhel, Natasha V.
author_facet Ung, Nolan
Brown, Michelle Q.
Hicks, Glenn R.
Raikhel, Natasha V.
author_sort Ung, Nolan
collection PubMed
description Tip growth of pollen tubes and root hairs occurs via rapid polar growth. These rapidly elongating cells require tip-focused endomembrane trafficking for the deposition and recycling of proteins, membranes, and cell wall materials. Most of the image-based data published to date are subjective and non-quantified. Quantitative and comparative descriptors of these highly dynamic processes have been a major challenge, but are highly desirable for genetic and chemical genomics approaches to dissect this biological network. To address this problem, we screened for small molecules that perturbed the localization of a marker for the Golgi Ras-like monomeric G-protein RAB2:GFP expressed in transgenic tobacco pollen. Semi-automated high-throughput imaging and image analysis resulted in the identification of novel compounds that altered pollen tube development and endomembrane trafficking. Six compounds that caused mislocalization and varying degrees of altered movement of RAB2:GFP-labeled endomembrane bodies were used to generate a training set of image data from which to quantify vesicle dynamics. The area, velocity, straightness, and intensity of each body were quantified using semi-automated image analysis tools revealing quantitative differences in the phenotype caused by each compound. A score was then given to each compound enabling quantitative comparisons between compounds. Our results demonstrate that image analysis can be used to quantitatively evaluate dynamic subcellular endomembrane phenotypes induced by bioactive chemicals, mutations, or other perturbing agents as part of a strategy to quantitatively dissect the endomembrane network.
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spelling pubmed-71052052020-03-31 An Approach to Quantify Endomembrane Dynamics in Pollen Utilizing Bioactive Chemicals Ung, Nolan Brown, Michelle Q. Hicks, Glenn R. Raikhel, Natasha V. Mol Plant Research Article Tip growth of pollen tubes and root hairs occurs via rapid polar growth. These rapidly elongating cells require tip-focused endomembrane trafficking for the deposition and recycling of proteins, membranes, and cell wall materials. Most of the image-based data published to date are subjective and non-quantified. Quantitative and comparative descriptors of these highly dynamic processes have been a major challenge, but are highly desirable for genetic and chemical genomics approaches to dissect this biological network. To address this problem, we screened for small molecules that perturbed the localization of a marker for the Golgi Ras-like monomeric G-protein RAB2:GFP expressed in transgenic tobacco pollen. Semi-automated high-throughput imaging and image analysis resulted in the identification of novel compounds that altered pollen tube development and endomembrane trafficking. Six compounds that caused mislocalization and varying degrees of altered movement of RAB2:GFP-labeled endomembrane bodies were used to generate a training set of image data from which to quantify vesicle dynamics. The area, velocity, straightness, and intensity of each body were quantified using semi-automated image analysis tools revealing quantitative differences in the phenotype caused by each compound. A score was then given to each compound enabling quantitative comparisons between compounds. Our results demonstrate that image analysis can be used to quantitatively evaluate dynamic subcellular endomembrane phenotypes induced by bioactive chemicals, mutations, or other perturbing agents as part of a strategy to quantitatively dissect the endomembrane network. The Authors. 2013-07 2015-01-05 /pmc/articles/PMC7105205/ /pubmed/23118478 http://dx.doi.org/10.1093/mp/sss092 Text en Copyright © 2013 The Authors. All rights reserved. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Research Article
Ung, Nolan
Brown, Michelle Q.
Hicks, Glenn R.
Raikhel, Natasha V.
An Approach to Quantify Endomembrane Dynamics in Pollen Utilizing Bioactive Chemicals
title An Approach to Quantify Endomembrane Dynamics in Pollen Utilizing Bioactive Chemicals
title_full An Approach to Quantify Endomembrane Dynamics in Pollen Utilizing Bioactive Chemicals
title_fullStr An Approach to Quantify Endomembrane Dynamics in Pollen Utilizing Bioactive Chemicals
title_full_unstemmed An Approach to Quantify Endomembrane Dynamics in Pollen Utilizing Bioactive Chemicals
title_short An Approach to Quantify Endomembrane Dynamics in Pollen Utilizing Bioactive Chemicals
title_sort approach to quantify endomembrane dynamics in pollen utilizing bioactive chemicals
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7105205/
https://www.ncbi.nlm.nih.gov/pubmed/23118478
http://dx.doi.org/10.1093/mp/sss092
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