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Inferring mitochondrial and cytosolic metabolism by coupling isotope tracing and deconvolution
The inability to inspect metabolic activities within distinct subcellular compartments has been a major barrier to our understanding of eukaryotic cell metabolism. Previous work addressed this challenge by analyzing metabolism in isolated organelles, which grossly bias metabolic activity. Here, we d...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10657349/ https://www.ncbi.nlm.nih.gov/pubmed/37980339 http://dx.doi.org/10.1038/s41467-023-42824-z |
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author | Stern, Alon Fokra, Mariam Sarvin, Boris Alrahem, Ahmad Abed Lee, Won Dong Aizenshtein, Elina Sarvin, Nikita Shlomi, Tomer |
author_facet | Stern, Alon Fokra, Mariam Sarvin, Boris Alrahem, Ahmad Abed Lee, Won Dong Aizenshtein, Elina Sarvin, Nikita Shlomi, Tomer |
author_sort | Stern, Alon |
collection | PubMed |
description | The inability to inspect metabolic activities within distinct subcellular compartments has been a major barrier to our understanding of eukaryotic cell metabolism. Previous work addressed this challenge by analyzing metabolism in isolated organelles, which grossly bias metabolic activity. Here, we describe a method for inferring physiological metabolic fluxes and metabolite concentrations in mitochondria and cytosol based on isotope tracing experiments performed with intact cells. This is made possible by computational deconvolution of metabolite isotopic labeling patterns and concentrations into cytosolic and mitochondrial counterparts, coupled with metabolic and thermodynamic modelling. Our approach lowers the uncertainty regarding compartmentalized fluxes and concentrations by one and three orders of magnitude compared to existing modelling approaches, respectively. We derive a quantitative view of mitochondrial and cytosolic metabolic activities in central carbon metabolism across cultured cell lines without performing cell fractionation, finding major variability in compartmentalized malate-aspartate shuttle fluxes. We expect our approach for inferring metabolism at a subcellular resolution to be instrumental for a variety of studies of metabolic dysfunction in human disease and for bioengineering. |
format | Online Article Text |
id | pubmed-10657349 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-106573492023-11-18 Inferring mitochondrial and cytosolic metabolism by coupling isotope tracing and deconvolution Stern, Alon Fokra, Mariam Sarvin, Boris Alrahem, Ahmad Abed Lee, Won Dong Aizenshtein, Elina Sarvin, Nikita Shlomi, Tomer Nat Commun Article The inability to inspect metabolic activities within distinct subcellular compartments has been a major barrier to our understanding of eukaryotic cell metabolism. Previous work addressed this challenge by analyzing metabolism in isolated organelles, which grossly bias metabolic activity. Here, we describe a method for inferring physiological metabolic fluxes and metabolite concentrations in mitochondria and cytosol based on isotope tracing experiments performed with intact cells. This is made possible by computational deconvolution of metabolite isotopic labeling patterns and concentrations into cytosolic and mitochondrial counterparts, coupled with metabolic and thermodynamic modelling. Our approach lowers the uncertainty regarding compartmentalized fluxes and concentrations by one and three orders of magnitude compared to existing modelling approaches, respectively. We derive a quantitative view of mitochondrial and cytosolic metabolic activities in central carbon metabolism across cultured cell lines without performing cell fractionation, finding major variability in compartmentalized malate-aspartate shuttle fluxes. We expect our approach for inferring metabolism at a subcellular resolution to be instrumental for a variety of studies of metabolic dysfunction in human disease and for bioengineering. Nature Publishing Group UK 2023-11-18 /pmc/articles/PMC10657349/ /pubmed/37980339 http://dx.doi.org/10.1038/s41467-023-42824-z Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Stern, Alon Fokra, Mariam Sarvin, Boris Alrahem, Ahmad Abed Lee, Won Dong Aizenshtein, Elina Sarvin, Nikita Shlomi, Tomer Inferring mitochondrial and cytosolic metabolism by coupling isotope tracing and deconvolution |
title | Inferring mitochondrial and cytosolic metabolism by coupling isotope tracing and deconvolution |
title_full | Inferring mitochondrial and cytosolic metabolism by coupling isotope tracing and deconvolution |
title_fullStr | Inferring mitochondrial and cytosolic metabolism by coupling isotope tracing and deconvolution |
title_full_unstemmed | Inferring mitochondrial and cytosolic metabolism by coupling isotope tracing and deconvolution |
title_short | Inferring mitochondrial and cytosolic metabolism by coupling isotope tracing and deconvolution |
title_sort | inferring mitochondrial and cytosolic metabolism by coupling isotope tracing and deconvolution |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10657349/ https://www.ncbi.nlm.nih.gov/pubmed/37980339 http://dx.doi.org/10.1038/s41467-023-42824-z |
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