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A Mathematical Model for Enzyme Clustering in Glucose Metabolism

We have recently demonstrated that the rate-limiting enzymes in human glucose metabolism organize into cytoplasmic clusters to form a multienzyme complex, the glucosome, in at least three different sizes. Quantitative high-content imaging data support a hypothesis that the glucosome clusters regulat...

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Autores principales: Jeon, Miji, Kang, Hye-Won, An, Songon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5807315/
https://www.ncbi.nlm.nih.gov/pubmed/29426820
http://dx.doi.org/10.1038/s41598-018-20348-7
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author Jeon, Miji
Kang, Hye-Won
An, Songon
author_facet Jeon, Miji
Kang, Hye-Won
An, Songon
author_sort Jeon, Miji
collection PubMed
description We have recently demonstrated that the rate-limiting enzymes in human glucose metabolism organize into cytoplasmic clusters to form a multienzyme complex, the glucosome, in at least three different sizes. Quantitative high-content imaging data support a hypothesis that the glucosome clusters regulate the direction of glucose flux between energy metabolism and building block biosynthesis in a cluster size-dependent manner. However, direct measurement of their functional contributions to cellular metabolism at subcellular levels has remained challenging. In this work, we develop a mathematical model using a system of ordinary differential equations, in which the association of the rate-limiting enzymes into multienzyme complexes is included as an essential element. We then demonstrate that our mathematical model provides a quantitative principle to simulate glucose flux at both subcellular and population levels in human cancer cells. Lastly, we use the model to simulate 2-deoxyglucose-mediated alteration of glucose flux in a population level based on subcellular high-content imaging data. Collectively, we introduce a new mathematical model for human glucose metabolism, which promotes our understanding of functional roles of differently sized multienzyme complexes in both single-cell and population levels.
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spelling pubmed-58073152018-02-14 A Mathematical Model for Enzyme Clustering in Glucose Metabolism Jeon, Miji Kang, Hye-Won An, Songon Sci Rep Article We have recently demonstrated that the rate-limiting enzymes in human glucose metabolism organize into cytoplasmic clusters to form a multienzyme complex, the glucosome, in at least three different sizes. Quantitative high-content imaging data support a hypothesis that the glucosome clusters regulate the direction of glucose flux between energy metabolism and building block biosynthesis in a cluster size-dependent manner. However, direct measurement of their functional contributions to cellular metabolism at subcellular levels has remained challenging. In this work, we develop a mathematical model using a system of ordinary differential equations, in which the association of the rate-limiting enzymes into multienzyme complexes is included as an essential element. We then demonstrate that our mathematical model provides a quantitative principle to simulate glucose flux at both subcellular and population levels in human cancer cells. Lastly, we use the model to simulate 2-deoxyglucose-mediated alteration of glucose flux in a population level based on subcellular high-content imaging data. Collectively, we introduce a new mathematical model for human glucose metabolism, which promotes our understanding of functional roles of differently sized multienzyme complexes in both single-cell and population levels. Nature Publishing Group UK 2018-02-09 /pmc/articles/PMC5807315/ /pubmed/29426820 http://dx.doi.org/10.1038/s41598-018-20348-7 Text en © The Author(s) 2018 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Jeon, Miji
Kang, Hye-Won
An, Songon
A Mathematical Model for Enzyme Clustering in Glucose Metabolism
title A Mathematical Model for Enzyme Clustering in Glucose Metabolism
title_full A Mathematical Model for Enzyme Clustering in Glucose Metabolism
title_fullStr A Mathematical Model for Enzyme Clustering in Glucose Metabolism
title_full_unstemmed A Mathematical Model for Enzyme Clustering in Glucose Metabolism
title_short A Mathematical Model for Enzyme Clustering in Glucose Metabolism
title_sort mathematical model for enzyme clustering in glucose metabolism
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5807315/
https://www.ncbi.nlm.nih.gov/pubmed/29426820
http://dx.doi.org/10.1038/s41598-018-20348-7
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