Quantitative 3D-imaging for cell biology and ecology of environmental microbial eukaryotes

We present a 3D-fluorescence imaging and classification tool for high throughput analysis of microbial eukaryotes in environmental samples. It entails high-content feature extraction that permits accurate automated taxonomic classification and quantitative data about organism ultrastructures and int...

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Detalles Bibliográficos
Autores principales: Colin, Sebastien, Coelho, Luis Pedro, Sunagawa, Shinichi, Bowler, Chris, Karsenti, Eric, Bork, Peer, Pepperkok, Rainer, de Vargas, Colomban
Formato: Online Artículo Texto
Lenguaje:English
Publicado: eLife Sciences Publications, Ltd 2017
Materias:
Cell Biology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5663481/
https://www.ncbi.nlm.nih.gov/pubmed/29087936
http://dx.doi.org/10.7554/eLife.26066
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author Colin, Sebastien
Coelho, Luis Pedro
Sunagawa, Shinichi
Bowler, Chris
Karsenti, Eric
Bork, Peer
Pepperkok, Rainer
de Vargas, Colomban
author_facet Colin, Sebastien
Coelho, Luis Pedro
Sunagawa, Shinichi
Bowler, Chris
Karsenti, Eric
Bork, Peer
Pepperkok, Rainer
de Vargas, Colomban
author_sort Colin, Sebastien
collection PubMed
description We present a 3D-fluorescence imaging and classification tool for high throughput analysis of microbial eukaryotes in environmental samples. It entails high-content feature extraction that permits accurate automated taxonomic classification and quantitative data about organism ultrastructures and interactions. Using plankton samples from the Tara Oceans expeditions, we validate its applicability to taxonomic profiling and ecosystem analyses, and discuss its potential for future integration of eukaryotic cell biology into evolutionary and ecological studies.
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spelling pubmed-56634812017-11-01 Quantitative 3D-imaging for cell biology and ecology of environmental microbial eukaryotes Colin, Sebastien Coelho, Luis Pedro Sunagawa, Shinichi Bowler, Chris Karsenti, Eric Bork, Peer Pepperkok, Rainer de Vargas, Colomban eLife Cell Biology We present a 3D-fluorescence imaging and classification tool for high throughput analysis of microbial eukaryotes in environmental samples. It entails high-content feature extraction that permits accurate automated taxonomic classification and quantitative data about organism ultrastructures and interactions. Using plankton samples from the Tara Oceans expeditions, we validate its applicability to taxonomic profiling and ecosystem analyses, and discuss its potential for future integration of eukaryotic cell biology into evolutionary and ecological studies. eLife Sciences Publications, Ltd 2017-10-31 /pmc/articles/PMC5663481/ /pubmed/29087936 http://dx.doi.org/10.7554/eLife.26066 Text en © 2017, Colin 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 Cell Biology
Colin, Sebastien
Coelho, Luis Pedro
Sunagawa, Shinichi
Bowler, Chris
Karsenti, Eric
Bork, Peer
Pepperkok, Rainer
de Vargas, Colomban
Quantitative 3D-imaging for cell biology and ecology of environmental microbial eukaryotes
title Quantitative 3D-imaging for cell biology and ecology of environmental microbial eukaryotes
title_full Quantitative 3D-imaging for cell biology and ecology of environmental microbial eukaryotes
title_fullStr Quantitative 3D-imaging for cell biology and ecology of environmental microbial eukaryotes
title_full_unstemmed Quantitative 3D-imaging for cell biology and ecology of environmental microbial eukaryotes
title_short Quantitative 3D-imaging for cell biology and ecology of environmental microbial eukaryotes
title_sort quantitative 3d-imaging for cell biology and ecology of environmental microbial eukaryotes
topic Cell Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5663481/
https://www.ncbi.nlm.nih.gov/pubmed/29087936
http://dx.doi.org/10.7554/eLife.26066
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