Kolodkin, A, Sahin, N, Phillips, A et al. (4 more authors) (2013) Optimization of stress response through the nuclear receptor-mediated cortisol signalling network. Nature Communications, 4 (1). ARTN 1792. ISSN 2041-1723
Abstract
It is an accepted paradigm that extended stress predisposes an individual to pathophysiology. However, the biological adaptations to minimize this risk are poorly understood. Using a computational model based upon realistic kinetic parameters we are able to reproduce the interaction of the stress hormone cortisol with its two nuclear receptors, the high-affinity glucocorticoid receptor and the low-affinity pregnane X-receptor. We demonstrate that regulatory signals between these two nuclear receptors are necessary to optimize the body’s response to stress episodes, attenuating both the magnitude and duration of the biological response. In addition, we predict that the activation of pregnane X-receptor by multiple, low-affinity endobiotic ligands is necessary for the significant pregnane X-receptor-mediated transcriptional response observed following stress episodes. This integration allows responses mediated through both the high and low-affinity nuclear receptors, which we predict is an important strategy to minimize the risk of disease from chronic stress.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | (c) 2013 Macmillan Publishers Limited. All rights reserved. This work is licensed under a Creative Commons AttributionNonCommercial-ShareAlike 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/3.0/ |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Biological Sciences (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 08 Apr 2019 14:16 |
Last Modified: | 08 Apr 2019 14:16 |
Status: | Published |
Publisher: | Nature Research |
Identification Number: | 10.1038/ncomms2799 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:125257 |
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Licence: CC-BY-NC-SA 3.0