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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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American Association for the Advancement of Science
2023
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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. |
format | Online Article Text |
id | pubmed-10431717 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | American Association for the Advancement of Science |
record_format | MEDLINE/PubMed |
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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