Determinants of brain cell metabolic phenotypes and energy substrate utilization unraveled with a modeling approach.
| Title: | Determinants of brain cell metabolic phenotypes and energy substrate utilization unraveled with a modeling approach. |
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| Authors: | Aitana Neves, Robert Costalat, Luc Pellerin |
| Source: | PLoS Computational Biology, Vol 8, Iss 9, p e1002686 (2012) |
| Publisher Information: | Public Library of Science (PLoS), 2012. |
| Publication Year: | 2012 |
| Collection: | LCC:Biology (General) |
| Subject Terms: | Biology (General), QH301-705.5 |
| More Details: | Although all brain cells bear in principle a comparable potential in terms of energetics, in reality they exhibit different metabolic profiles. The specific biochemical characteristics explaining such disparities and their relative importance are largely unknown. Using a modeling approach, we show that modifying the kinetic parameters of pyruvate dehydrogenase and mitochondrial NADH shuttling within a realistic interval can yield a striking switch in lactate flux direction. In this context, cells having essentially an oxidative profile exhibit pronounced extracellular lactate uptake and consumption. However, they can be turned into cells with prominent aerobic glycolysis by selectively reducing the aforementioned parameters. In the case of primarily oxidative cells, we also examined the role of glycolysis and lactate transport in providing pyruvate to mitochondria in order to sustain oxidative phosphorylation. The results show that changes in lactate transport capacity and extracellular lactate concentration within the range described experimentally can sustain enhanced oxidative metabolism upon activation. Such a demonstration provides key elements to understand why certain brain cell types constitutively adopt a particular metabolic profile and how specific features can be altered under different physiological and pathological conditions in order to face evolving energy demands. |
| Document Type: | article |
| File Description: | electronic resource |
| Language: | English |
| ISSN: | 1553-734X 1553-7358 |
| Relation: | http://europepmc.org/articles/PMC3441424?pdf=render; https://doaj.org/toc/1553-734X; https://doaj.org/toc/1553-7358 |
| DOI: | 10.1371/journal.pcbi.1002686 |
| Access URL: | https://doaj.org/article/269eee73c51c4333b7853cb56bbf25ea |
| Accession Number: | edsdoj.269eee73c51c4333b7853cb56bbf25ea |
| Database: | Directory of Open Access Journals |
| ISSN: | 1553734X 15537358 |
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| DOI: | 10.1371/journal.pcbi.1002686 |
| Published in: | PLoS Computational Biology |
| Language: | English |