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Junction Mapper is a novel computer vision tool to decipher cell–cell contact phenotypes

Stable cell–cell contacts underpin tissue architecture and organization. Quantification of junctions of mammalian epithelia requires laborious manual measurements that are a major roadblock for mechanistic studies. We designed Junction Mapper as an open access, semi-automated software that defines t...

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Autores principales: Brezovjakova, Helena, Tomlinson, Chris, Mohd Naim, Noor, Swiatlowska, Pamela, Erasmus, Jennifer C, Huveneers, Stephan, Gorelik, Julia, Bruche, Susann, Braga, Vania MM
Formato: Online Artículo Texto
Lenguaje:English
Publicado: eLife Sciences Publications, Ltd 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7034980/
https://www.ncbi.nlm.nih.gov/pubmed/31793877
http://dx.doi.org/10.7554/eLife.45413
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author Brezovjakova, Helena
Tomlinson, Chris
Mohd Naim, Noor
Swiatlowska, Pamela
Erasmus, Jennifer C
Huveneers, Stephan
Gorelik, Julia
Bruche, Susann
Braga, Vania MM
author_facet Brezovjakova, Helena
Tomlinson, Chris
Mohd Naim, Noor
Swiatlowska, Pamela
Erasmus, Jennifer C
Huveneers, Stephan
Gorelik, Julia
Bruche, Susann
Braga, Vania MM
author_sort Brezovjakova, Helena
collection PubMed
description Stable cell–cell contacts underpin tissue architecture and organization. Quantification of junctions of mammalian epithelia requires laborious manual measurements that are a major roadblock for mechanistic studies. We designed Junction Mapper as an open access, semi-automated software that defines the status of adhesiveness via the simultaneous measurement of pre-defined parameters at cell–cell contacts. It identifies contacting interfaces and corners with minimal user input and quantifies length, area and intensity of junction markers. Its ability to measure fragmented junctions is unique. Importantly, junctions that considerably deviate from the contiguous staining and straight contact phenotype seen in epithelia are also successfully quantified (i.e. cardiomyocytes or endothelia). Distinct phenotypes of junction disruption can be clearly differentiated among various oncogenes, depletion of actin regulators or stimulation with other agents. Junction Mapper is thus a powerful, unbiased and highly applicable software for profiling cell–cell adhesion phenotypes and facilitate studies on junction dynamics in health and disease.
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spelling pubmed-70349802020-02-24 Junction Mapper is a novel computer vision tool to decipher cell–cell contact phenotypes Brezovjakova, Helena Tomlinson, Chris Mohd Naim, Noor Swiatlowska, Pamela Erasmus, Jennifer C Huveneers, Stephan Gorelik, Julia Bruche, Susann Braga, Vania MM eLife Cancer Biology Stable cell–cell contacts underpin tissue architecture and organization. Quantification of junctions of mammalian epithelia requires laborious manual measurements that are a major roadblock for mechanistic studies. We designed Junction Mapper as an open access, semi-automated software that defines the status of adhesiveness via the simultaneous measurement of pre-defined parameters at cell–cell contacts. It identifies contacting interfaces and corners with minimal user input and quantifies length, area and intensity of junction markers. Its ability to measure fragmented junctions is unique. Importantly, junctions that considerably deviate from the contiguous staining and straight contact phenotype seen in epithelia are also successfully quantified (i.e. cardiomyocytes or endothelia). Distinct phenotypes of junction disruption can be clearly differentiated among various oncogenes, depletion of actin regulators or stimulation with other agents. Junction Mapper is thus a powerful, unbiased and highly applicable software for profiling cell–cell adhesion phenotypes and facilitate studies on junction dynamics in health and disease. eLife Sciences Publications, Ltd 2019-12-03 /pmc/articles/PMC7034980/ /pubmed/31793877 http://dx.doi.org/10.7554/eLife.45413 Text en © 2019, Brezovjakova et al http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited.
spellingShingle Cancer Biology
Brezovjakova, Helena
Tomlinson, Chris
Mohd Naim, Noor
Swiatlowska, Pamela
Erasmus, Jennifer C
Huveneers, Stephan
Gorelik, Julia
Bruche, Susann
Braga, Vania MM
Junction Mapper is a novel computer vision tool to decipher cell–cell contact phenotypes
title Junction Mapper is a novel computer vision tool to decipher cell–cell contact phenotypes
title_full Junction Mapper is a novel computer vision tool to decipher cell–cell contact phenotypes
title_fullStr Junction Mapper is a novel computer vision tool to decipher cell–cell contact phenotypes
title_full_unstemmed Junction Mapper is a novel computer vision tool to decipher cell–cell contact phenotypes
title_short Junction Mapper is a novel computer vision tool to decipher cell–cell contact phenotypes
title_sort junction mapper is a novel computer vision tool to decipher cell–cell contact phenotypes
topic Cancer Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7034980/
https://www.ncbi.nlm.nih.gov/pubmed/31793877
http://dx.doi.org/10.7554/eLife.45413
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