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Cellular cartography of the organ of Corti based on optical tissue clearing and machine learning
The highly organized spatial arrangement of sensory hair cells in the organ of Corti is essential for inner ear function. Here, we report a new analytical pipeline, based on optical clearing of tissue, for the construction of a single-cell resolution map of the organ of Corti. A sorbitol-based optic...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6338463/ https://www.ncbi.nlm.nih.gov/pubmed/30657453 http://dx.doi.org/10.7554/eLife.40946 |
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author | Urata, Shinji Iida, Tadatsune Yamamoto, Masamichi Mizushima, Yu Fujimoto, Chisato Matsumoto, Yu Yamasoba, Tatsuya Okabe, Shigeo |
author_facet | Urata, Shinji Iida, Tadatsune Yamamoto, Masamichi Mizushima, Yu Fujimoto, Chisato Matsumoto, Yu Yamasoba, Tatsuya Okabe, Shigeo |
author_sort | Urata, Shinji |
collection | PubMed |
description | The highly organized spatial arrangement of sensory hair cells in the organ of Corti is essential for inner ear function. Here, we report a new analytical pipeline, based on optical clearing of tissue, for the construction of a single-cell resolution map of the organ of Corti. A sorbitol-based optical clearing method enabled imaging of the entire cochlea at subcellular resolution. High-fidelity detection and analysis of all hair cell positions along the entire longitudinal axis of the organ of Corti were performed automatically by machine learning–based pattern recognition. Application of this method to samples from young, adult, and noise-exposed mice extracted essential information regarding cellular pathology, including longitudinal and radial spatial characteristics of cell loss, implying that multiple mechanisms underlie clustered cell loss. Our method of cellular mapping is effective for system-level phenotyping of the organ of Corti under both physiological and pathological conditions. |
format | Online Article Text |
id | pubmed-6338463 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-63384632019-01-24 Cellular cartography of the organ of Corti based on optical tissue clearing and machine learning Urata, Shinji Iida, Tadatsune Yamamoto, Masamichi Mizushima, Yu Fujimoto, Chisato Matsumoto, Yu Yamasoba, Tatsuya Okabe, Shigeo eLife Neuroscience The highly organized spatial arrangement of sensory hair cells in the organ of Corti is essential for inner ear function. Here, we report a new analytical pipeline, based on optical clearing of tissue, for the construction of a single-cell resolution map of the organ of Corti. A sorbitol-based optical clearing method enabled imaging of the entire cochlea at subcellular resolution. High-fidelity detection and analysis of all hair cell positions along the entire longitudinal axis of the organ of Corti were performed automatically by machine learning–based pattern recognition. Application of this method to samples from young, adult, and noise-exposed mice extracted essential information regarding cellular pathology, including longitudinal and radial spatial characteristics of cell loss, implying that multiple mechanisms underlie clustered cell loss. Our method of cellular mapping is effective for system-level phenotyping of the organ of Corti under both physiological and pathological conditions. eLife Sciences Publications, Ltd 2019-01-18 /pmc/articles/PMC6338463/ /pubmed/30657453 http://dx.doi.org/10.7554/eLife.40946 Text en © 2019, Urata 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 | Neuroscience Urata, Shinji Iida, Tadatsune Yamamoto, Masamichi Mizushima, Yu Fujimoto, Chisato Matsumoto, Yu Yamasoba, Tatsuya Okabe, Shigeo Cellular cartography of the organ of Corti based on optical tissue clearing and machine learning |
title | Cellular cartography of the organ of Corti based on optical tissue clearing and machine learning |
title_full | Cellular cartography of the organ of Corti based on optical tissue clearing and machine learning |
title_fullStr | Cellular cartography of the organ of Corti based on optical tissue clearing and machine learning |
title_full_unstemmed | Cellular cartography of the organ of Corti based on optical tissue clearing and machine learning |
title_short | Cellular cartography of the organ of Corti based on optical tissue clearing and machine learning |
title_sort | cellular cartography of the organ of corti based on optical tissue clearing and machine learning |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6338463/ https://www.ncbi.nlm.nih.gov/pubmed/30657453 http://dx.doi.org/10.7554/eLife.40946 |
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