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Profiling single cancer cell metabolism via high-content SRS imaging with chemical sparsity

Metabolic reprogramming in a subpopulation of cancer cells is a hallmark of tumor chemoresistance. However, single-cell metabolic profiling is difficult because of the lack of a method that can simultaneously detect multiple metabolites at the single-cell level. In this study, through hyperspectral...

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Autores principales: Tan, Yuying, Lin, Haonan, Cheng, Ji-Xin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Association for the Advancement of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10431717/
https://www.ncbi.nlm.nih.gov/pubmed/37585522
http://dx.doi.org/10.1126/sciadv.adg6061
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author Tan, Yuying
Lin, Haonan
Cheng, Ji-Xin
author_facet Tan, Yuying
Lin, Haonan
Cheng, Ji-Xin
author_sort Tan, Yuying
collection PubMed
description Metabolic reprogramming in a subpopulation of cancer cells is a hallmark of tumor chemoresistance. However, single-cell metabolic profiling is difficult because of the lack of a method that can simultaneously detect multiple metabolites at the single-cell level. In this study, through hyperspectral stimulated Raman scattering (hSRS) imaging in the carbon-hydrogen (C–H) window and sparsity-driven hyperspectral image decomposition, we demonstrate a high-content hSRS (h(2)SRS) imaging approach that enables the simultaneous mapping of five major biomolecules, including proteins, carbohydrates, fatty acids, cholesterol, and nucleic acids at the single-cell level. h(2)SRS imaging of brain and pancreatic cancer cells under chemotherapy revealed acute and adapted chemotherapy-induced metabolic reprogramming and the unique metabolic features of chemoresistance. Our approach is expected to facilitate the discovery of therapeutic targets to combat chemoresistance. This study illustrates a high-content, label-free chemical imaging approach that measures metabolic profiles at the single-cell level and warrants further research on cellular metabolism.
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spelling pubmed-104317172023-08-17 Profiling single cancer cell metabolism via high-content SRS imaging with chemical sparsity Tan, Yuying Lin, Haonan Cheng, Ji-Xin Sci Adv Physical and Materials Sciences Metabolic reprogramming in a subpopulation of cancer cells is a hallmark of tumor chemoresistance. However, single-cell metabolic profiling is difficult because of the lack of a method that can simultaneously detect multiple metabolites at the single-cell level. In this study, through hyperspectral stimulated Raman scattering (hSRS) imaging in the carbon-hydrogen (C–H) window and sparsity-driven hyperspectral image decomposition, we demonstrate a high-content hSRS (h(2)SRS) imaging approach that enables the simultaneous mapping of five major biomolecules, including proteins, carbohydrates, fatty acids, cholesterol, and nucleic acids at the single-cell level. h(2)SRS imaging of brain and pancreatic cancer cells under chemotherapy revealed acute and adapted chemotherapy-induced metabolic reprogramming and the unique metabolic features of chemoresistance. Our approach is expected to facilitate the discovery of therapeutic targets to combat chemoresistance. This study illustrates a high-content, label-free chemical imaging approach that measures metabolic profiles at the single-cell level and warrants further research on cellular metabolism. American Association for the Advancement of Science 2023-08-16 /pmc/articles/PMC10431717/ /pubmed/37585522 http://dx.doi.org/10.1126/sciadv.adg6061 Text en Copyright © 2023 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC). https://creativecommons.org/licenses/by-nc/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license (https://creativecommons.org/licenses/by-nc/4.0/) , which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited.
spellingShingle Physical and Materials Sciences
Tan, Yuying
Lin, Haonan
Cheng, Ji-Xin
Profiling single cancer cell metabolism via high-content SRS imaging with chemical sparsity
title Profiling single cancer cell metabolism via high-content SRS imaging with chemical sparsity
title_full Profiling single cancer cell metabolism via high-content SRS imaging with chemical sparsity
title_fullStr Profiling single cancer cell metabolism via high-content SRS imaging with chemical sparsity
title_full_unstemmed Profiling single cancer cell metabolism via high-content SRS imaging with chemical sparsity
title_short Profiling single cancer cell metabolism via high-content SRS imaging with chemical sparsity
title_sort profiling single cancer cell metabolism via high-content srs imaging with chemical sparsity
topic Physical and Materials Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10431717/
https://www.ncbi.nlm.nih.gov/pubmed/37585522
http://dx.doi.org/10.1126/sciadv.adg6061
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