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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...

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Autores principales: 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.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
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.
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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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