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Computational Modeling and Imaging of the Intracellular Oxygen Gradient
Computational modeling can provide a mechanistic and quantitative framework for describing intracellular spatial heterogeneity of solutes such as oxygen partial pressure (pO(2)). This study develops and evaluates a finite-element model of oxygen-consuming mitochondrial bioenergetics using the COMSOL...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9604273/ https://www.ncbi.nlm.nih.gov/pubmed/36293452 http://dx.doi.org/10.3390/ijms232012597 |
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author | Sedlack, Andrew J. H. Penjweini, Rozhin Link, Katie A. Brown, Alexandra Kim, Jeonghan Park, Sung-Jun Chung, Jay H. Morgan, Nicole Y. Knutson, Jay R. |
author_facet | Sedlack, Andrew J. H. Penjweini, Rozhin Link, Katie A. Brown, Alexandra Kim, Jeonghan Park, Sung-Jun Chung, Jay H. Morgan, Nicole Y. Knutson, Jay R. |
author_sort | Sedlack, Andrew J. H. |
collection | PubMed |
description | Computational modeling can provide a mechanistic and quantitative framework for describing intracellular spatial heterogeneity of solutes such as oxygen partial pressure (pO(2)). This study develops and evaluates a finite-element model of oxygen-consuming mitochondrial bioenergetics using the COMSOL Multiphysics program. The model derives steady-state oxygen (O(2)) distributions from Fickian diffusion and Michaelis–Menten consumption kinetics in the mitochondria and cytoplasm. Intrinsic model parameters such as diffusivity and maximum consumption rate were estimated from previously published values for isolated and intact mitochondria. The model was compared with experimental data collected for the intracellular and mitochondrial pO(2) levels in human cervical cancer cells (HeLa) in different respiratory states and under different levels of imposed pO(2). Experimental pO(2) gradients were measured using lifetime imaging of a Förster resonance energy transfer (FRET)-based O(2) sensor, Myoglobin-mCherry, which offers in situ real-time and noninvasive measurements of subcellular pO(2) in living cells. On the basis of these results, the model qualitatively predicted (1) the integrated experimental data from mitochondria under diverse experimental conditions, and (2) the impact of changes in one or more mitochondrial processes on overall bioenergetics. |
format | Online Article Text |
id | pubmed-9604273 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-96042732022-10-27 Computational Modeling and Imaging of the Intracellular Oxygen Gradient Sedlack, Andrew J. H. Penjweini, Rozhin Link, Katie A. Brown, Alexandra Kim, Jeonghan Park, Sung-Jun Chung, Jay H. Morgan, Nicole Y. Knutson, Jay R. Int J Mol Sci Article Computational modeling can provide a mechanistic and quantitative framework for describing intracellular spatial heterogeneity of solutes such as oxygen partial pressure (pO(2)). This study develops and evaluates a finite-element model of oxygen-consuming mitochondrial bioenergetics using the COMSOL Multiphysics program. The model derives steady-state oxygen (O(2)) distributions from Fickian diffusion and Michaelis–Menten consumption kinetics in the mitochondria and cytoplasm. Intrinsic model parameters such as diffusivity and maximum consumption rate were estimated from previously published values for isolated and intact mitochondria. The model was compared with experimental data collected for the intracellular and mitochondrial pO(2) levels in human cervical cancer cells (HeLa) in different respiratory states and under different levels of imposed pO(2). Experimental pO(2) gradients were measured using lifetime imaging of a Förster resonance energy transfer (FRET)-based O(2) sensor, Myoglobin-mCherry, which offers in situ real-time and noninvasive measurements of subcellular pO(2) in living cells. On the basis of these results, the model qualitatively predicted (1) the integrated experimental data from mitochondria under diverse experimental conditions, and (2) the impact of changes in one or more mitochondrial processes on overall bioenergetics. MDPI 2022-10-20 /pmc/articles/PMC9604273/ /pubmed/36293452 http://dx.doi.org/10.3390/ijms232012597 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Sedlack, Andrew J. H. Penjweini, Rozhin Link, Katie A. Brown, Alexandra Kim, Jeonghan Park, Sung-Jun Chung, Jay H. Morgan, Nicole Y. Knutson, Jay R. Computational Modeling and Imaging of the Intracellular Oxygen Gradient |
title | Computational Modeling and Imaging of the Intracellular Oxygen Gradient |
title_full | Computational Modeling and Imaging of the Intracellular Oxygen Gradient |
title_fullStr | Computational Modeling and Imaging of the Intracellular Oxygen Gradient |
title_full_unstemmed | Computational Modeling and Imaging of the Intracellular Oxygen Gradient |
title_short | Computational Modeling and Imaging of the Intracellular Oxygen Gradient |
title_sort | computational modeling and imaging of the intracellular oxygen gradient |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9604273/ https://www.ncbi.nlm.nih.gov/pubmed/36293452 http://dx.doi.org/10.3390/ijms232012597 |
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