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MicrobeJ, a tool for high throughput bacterial cell detection and quantitative analysis
Single cell analysis of bacteria and subcellular protein localization dynamics has shown that bacteria have elaborate life cycles, cytoskeletal protein networks, and complex signal transduction pathways driven by localized proteins. The volume of multi-dimensional images generated in such experiment...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5010025/ https://www.ncbi.nlm.nih.gov/pubmed/27572972 http://dx.doi.org/10.1038/nmicrobiol.2016.77 |
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author | Ducret, Adrien Quardokus, Ellen M. Brun, Yves V. |
author_facet | Ducret, Adrien Quardokus, Ellen M. Brun, Yves V. |
author_sort | Ducret, Adrien |
collection | PubMed |
description | Single cell analysis of bacteria and subcellular protein localization dynamics has shown that bacteria have elaborate life cycles, cytoskeletal protein networks, and complex signal transduction pathways driven by localized proteins. The volume of multi-dimensional images generated in such experiments and the computation time required to detect, associate, and track cells and subcellular features pose considerable challenges, especially for high-throughput experiments. Therefore, there is a need for a versatile, computationally efficient image analysis tool capable of extracting the desired relationships from images in a meaningful and unbiased way. Here we present MicrobeJ, a plug-in for the open-source platform ImageJ. MicrobeJ provides a comprehensive framework to process images derived from a wide variety of microscopy experiments with special emphasis on large image sets. It performs the most common intensity and morphology measurements as well as customized detection of poles, septa, fluorescent foci, and organelles, determines their sub-cellular localization with sub-pixel resolution, and tracks them over time. Because a dynamic link is maintained between the images, measurements, and all data representations derived from them, the editor and suite of advanced data presentation tools facilitates the image analysis process and provides a robust way to verify the accuracy and veracity of the data. |
format | Online Article Text |
id | pubmed-5010025 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
record_format | MEDLINE/PubMed |
spelling | pubmed-50100252016-12-20 MicrobeJ, a tool for high throughput bacterial cell detection and quantitative analysis Ducret, Adrien Quardokus, Ellen M. Brun, Yves V. Nat Microbiol Article Single cell analysis of bacteria and subcellular protein localization dynamics has shown that bacteria have elaborate life cycles, cytoskeletal protein networks, and complex signal transduction pathways driven by localized proteins. The volume of multi-dimensional images generated in such experiments and the computation time required to detect, associate, and track cells and subcellular features pose considerable challenges, especially for high-throughput experiments. Therefore, there is a need for a versatile, computationally efficient image analysis tool capable of extracting the desired relationships from images in a meaningful and unbiased way. Here we present MicrobeJ, a plug-in for the open-source platform ImageJ. MicrobeJ provides a comprehensive framework to process images derived from a wide variety of microscopy experiments with special emphasis on large image sets. It performs the most common intensity and morphology measurements as well as customized detection of poles, septa, fluorescent foci, and organelles, determines their sub-cellular localization with sub-pixel resolution, and tracks them over time. Because a dynamic link is maintained between the images, measurements, and all data representations derived from them, the editor and suite of advanced data presentation tools facilitates the image analysis process and provides a robust way to verify the accuracy and veracity of the data. 2016-06-20 /pmc/articles/PMC5010025/ /pubmed/27572972 http://dx.doi.org/10.1038/nmicrobiol.2016.77 Text en Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:http://www.nature.com/authors/editorial_policies/license.html#terms |
spellingShingle | Article Ducret, Adrien Quardokus, Ellen M. Brun, Yves V. MicrobeJ, a tool for high throughput bacterial cell detection and quantitative analysis |
title | MicrobeJ, a tool for high throughput bacterial cell detection and quantitative analysis |
title_full | MicrobeJ, a tool for high throughput bacterial cell detection and quantitative analysis |
title_fullStr | MicrobeJ, a tool for high throughput bacterial cell detection and quantitative analysis |
title_full_unstemmed | MicrobeJ, a tool for high throughput bacterial cell detection and quantitative analysis |
title_short | MicrobeJ, a tool for high throughput bacterial cell detection and quantitative analysis |
title_sort | microbej, a tool for high throughput bacterial cell detection and quantitative analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5010025/ https://www.ncbi.nlm.nih.gov/pubmed/27572972 http://dx.doi.org/10.1038/nmicrobiol.2016.77 |
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