Non-invasive cell classification using the Paint Raman Express Spectroscopy System (PRESS)

Abstract Raman scattering represents the distribution and abundance of intracellular molecules, including proteins and lipids, facilitating distinction between cellular states non-invasively and without staining. However, the scattered light obtained from cells is faint and cells have complex struct...

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Autores principales:	Yuka Akagi, Nobuhito Mori, Teruhisa Kawamura, Yuzo Takayama, Yasuyuki S. Kida
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/3476af3d7c6048a39ac1d37d819434bd
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spelling	oai:doaj.org-article:3476af3d7c6048a39ac1d37d819434bd2021-12-02T17:32:59ZNon-invasive cell classification using the Paint Raman Express Spectroscopy System (PRESS)10.1038/s41598-021-88056-32045-2322https://doaj.org/article/3476af3d7c6048a39ac1d37d819434bd2021-04-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-88056-3https://doaj.org/toc/2045-2322Abstract Raman scattering represents the distribution and abundance of intracellular molecules, including proteins and lipids, facilitating distinction between cellular states non-invasively and without staining. However, the scattered light obtained from cells is faint and cells have complex structures, making it difficult to obtain a Raman spectrum covering the entire cell in a short time using conventional methods. This also prevents efficient label-free cell classification. In the present study, we developed the Paint Raman Express Spectroscopy System, which uses two fast-rotating galvano mirrors to obtain spectra from a wide area of a cell. By using this system and applying machine learning, we were able to acquire broad spectra of a variety of human and mouse cell types, including pluripotent stem cells and confirmed that each cell type can be classified with high accuracy. Moreover, we classified different activation states of human T cells, despite their similar morphology. This system could be used for rapid and low-cost drug evaluation and quality management for drug screening in cell-based assays.Yuka AkagiNobuhito MoriTeruhisa KawamuraYuzo TakayamaYasuyuki S. KidaNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-15 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Yuka Akagi Nobuhito Mori Teruhisa Kawamura Yuzo Takayama Yasuyuki S. Kida Non-invasive cell classification using the Paint Raman Express Spectroscopy System (PRESS)
description	Abstract Raman scattering represents the distribution and abundance of intracellular molecules, including proteins and lipids, facilitating distinction between cellular states non-invasively and without staining. However, the scattered light obtained from cells is faint and cells have complex structures, making it difficult to obtain a Raman spectrum covering the entire cell in a short time using conventional methods. This also prevents efficient label-free cell classification. In the present study, we developed the Paint Raman Express Spectroscopy System, which uses two fast-rotating galvano mirrors to obtain spectra from a wide area of a cell. By using this system and applying machine learning, we were able to acquire broad spectra of a variety of human and mouse cell types, including pluripotent stem cells and confirmed that each cell type can be classified with high accuracy. Moreover, we classified different activation states of human T cells, despite their similar morphology. This system could be used for rapid and low-cost drug evaluation and quality management for drug screening in cell-based assays.
format	article
author	Yuka Akagi Nobuhito Mori Teruhisa Kawamura Yuzo Takayama Yasuyuki S. Kida
author_facet	Yuka Akagi Nobuhito Mori Teruhisa Kawamura Yuzo Takayama Yasuyuki S. Kida
author_sort	Yuka Akagi
title	Non-invasive cell classification using the Paint Raman Express Spectroscopy System (PRESS)
title_short	Non-invasive cell classification using the Paint Raman Express Spectroscopy System (PRESS)
title_full	Non-invasive cell classification using the Paint Raman Express Spectroscopy System (PRESS)
title_fullStr	Non-invasive cell classification using the Paint Raman Express Spectroscopy System (PRESS)
title_full_unstemmed	Non-invasive cell classification using the Paint Raman Express Spectroscopy System (PRESS)
title_sort	non-invasive cell classification using the paint raman express spectroscopy system (press)
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/3476af3d7c6048a39ac1d37d819434bd
work_keys_str_mv	AT yukaakagi noninvasivecellclassificationusingthepaintramanexpressspectroscopysystempress AT nobuhitomori noninvasivecellclassificationusingthepaintramanexpressspectroscopysystempress AT teruhisakawamura noninvasivecellclassificationusingthepaintramanexpressspectroscopysystempress AT yuzotakayama noninvasivecellclassificationusingthepaintramanexpressspectroscopysystempress AT yasuyukiskida noninvasivecellclassificationusingthepaintramanexpressspectroscopysystempress
_version_	1718380112152363008

Non-invasive cell classification using the Paint Raman Express Spectroscopy System (PRESS)

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