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Quantitative chemometric phenotyping of three-dimensional liver organoids by Raman spectral imaging
Confocal Raman spectral imaging (RSI) enables high-content, label-free visualization of a wide range of molecules in biological specimens without sample preparation. However, reliable quantification of the deconvoluted spectra is needed. Here we develop an integrated bioanalytical methodology, qRama...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10162950/ https://www.ncbi.nlm.nih.gov/pubmed/37159662 http://dx.doi.org/10.1016/j.crmeth.2023.100440 |
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author | LaLone, Vernon Aizenshtadt, Aleksandra Goertz, John Skottvoll, Frøydis Sved Mota, Marco Barbero You, Junji Zhao, Xiaoyu Berg, Henriette Engen Stokowiec, Justyna Yu, Minzhi Schwendeman, Anna Scholz, Hanne Wilson, Steven Ray Krauss, Stefan Stevens, Molly M. |
author_facet | LaLone, Vernon Aizenshtadt, Aleksandra Goertz, John Skottvoll, Frøydis Sved Mota, Marco Barbero You, Junji Zhao, Xiaoyu Berg, Henriette Engen Stokowiec, Justyna Yu, Minzhi Schwendeman, Anna Scholz, Hanne Wilson, Steven Ray Krauss, Stefan Stevens, Molly M. |
author_sort | LaLone, Vernon |
collection | PubMed |
description | Confocal Raman spectral imaging (RSI) enables high-content, label-free visualization of a wide range of molecules in biological specimens without sample preparation. However, reliable quantification of the deconvoluted spectra is needed. Here we develop an integrated bioanalytical methodology, qRamanomics, to qualify RSI as a tissue phantom calibrated tool for quantitative spatial chemotyping of major classes of biomolecules. Next, we apply qRamanomics to fixed 3D liver organoids generated from stem-cell-derived or primary hepatocytes to assess specimen variation and maturity. We then demonstrate the utility of qRamanomics for identifying biomolecular response signatures from a panel of liver-altering drugs, probing drug-induced compositional changes in 3D organoids followed by in situ monitoring of drug metabolism and accumulation. Quantitative chemometric phenotyping constitutes an important step in developing quantitative label-free interrogation of 3D biological specimens. |
format | Online Article Text |
id | pubmed-10162950 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-101629502023-05-07 Quantitative chemometric phenotyping of three-dimensional liver organoids by Raman spectral imaging LaLone, Vernon Aizenshtadt, Aleksandra Goertz, John Skottvoll, Frøydis Sved Mota, Marco Barbero You, Junji Zhao, Xiaoyu Berg, Henriette Engen Stokowiec, Justyna Yu, Minzhi Schwendeman, Anna Scholz, Hanne Wilson, Steven Ray Krauss, Stefan Stevens, Molly M. Cell Rep Methods Article Confocal Raman spectral imaging (RSI) enables high-content, label-free visualization of a wide range of molecules in biological specimens without sample preparation. However, reliable quantification of the deconvoluted spectra is needed. Here we develop an integrated bioanalytical methodology, qRamanomics, to qualify RSI as a tissue phantom calibrated tool for quantitative spatial chemotyping of major classes of biomolecules. Next, we apply qRamanomics to fixed 3D liver organoids generated from stem-cell-derived or primary hepatocytes to assess specimen variation and maturity. We then demonstrate the utility of qRamanomics for identifying biomolecular response signatures from a panel of liver-altering drugs, probing drug-induced compositional changes in 3D organoids followed by in situ monitoring of drug metabolism and accumulation. Quantitative chemometric phenotyping constitutes an important step in developing quantitative label-free interrogation of 3D biological specimens. Elsevier 2023-03-31 /pmc/articles/PMC10162950/ /pubmed/37159662 http://dx.doi.org/10.1016/j.crmeth.2023.100440 Text en © 2023 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article LaLone, Vernon Aizenshtadt, Aleksandra Goertz, John Skottvoll, Frøydis Sved Mota, Marco Barbero You, Junji Zhao, Xiaoyu Berg, Henriette Engen Stokowiec, Justyna Yu, Minzhi Schwendeman, Anna Scholz, Hanne Wilson, Steven Ray Krauss, Stefan Stevens, Molly M. Quantitative chemometric phenotyping of three-dimensional liver organoids by Raman spectral imaging |
title | Quantitative chemometric phenotyping of three-dimensional liver organoids by Raman spectral imaging |
title_full | Quantitative chemometric phenotyping of three-dimensional liver organoids by Raman spectral imaging |
title_fullStr | Quantitative chemometric phenotyping of three-dimensional liver organoids by Raman spectral imaging |
title_full_unstemmed | Quantitative chemometric phenotyping of three-dimensional liver organoids by Raman spectral imaging |
title_short | Quantitative chemometric phenotyping of three-dimensional liver organoids by Raman spectral imaging |
title_sort | quantitative chemometric phenotyping of three-dimensional liver organoids by raman spectral imaging |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10162950/ https://www.ncbi.nlm.nih.gov/pubmed/37159662 http://dx.doi.org/10.1016/j.crmeth.2023.100440 |
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