Modelling and mathematical analysis of the M2 receptor-dependent joint signalling and secondary messenger network in CHO cells

Engelhardt, B., Holze, J., Elliott, C. , Baillie, G.S. , Kschischo, M. and Fröhlich, H. (2018) Modelling and mathematical analysis of the M2 receptor-dependent joint signalling and secondary messenger network in CHO cells. Mathematical Medicine and Biology, 35(3), pp. 279-297. (doi: 10.1093/imammb/dqx003) (PMID:28505258)

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The muscarinic M2 receptor is a prominent member of the GPCR family and strongly involved in heart diseases. Recently published experimental work explored the cellular response to iperoxo-induced M2 receptor stimulation in Chinese hamster ovary (CHO) cells. To better understand these responses, we modelled and analysed the muscarinic M2 receptor-dependent signalling pathway combined with relevant secondary messenger molecules using mass action. In our literature-based joint signalling and secondary messenger model, all binding and phosphorylation events are explicitly taken into account in order to enable subsequent stoichiometric matrix analysis. We propose constraint flux sampling (CFS) as a method to characterize the expected shift of the steady state reaction flux distribution due to the known amount of cAMP production and PDE4 activation. CFS correctly predicts an experimentally observable influence on the cytoskeleton structure (marked by actin and tubulin) and in consequence a change of the optical density of cells. In a second step, we use CFS to simulate the effect of knock-out experiments within our biological system, and thus to rank the influence of individual molecules on the observed change of the optical cell density. In particular, we confirm the relevance of the protein RGS14, which is supported by current literature. A combination of CFS with Elementary Flux Mode analysis enabled us to determine the possible underlying mechanism. Our analysis suggests that mathematical tools developed for metabolic network analysis can also be applied to mixed secondary messenger and signalling models. This could be very helpful to perform model checking with little effort and to generate hypotheses for further research if parameters are not known.

Item Type:Articles
Glasgow Author(s) Enlighten ID:Elliott, Dr Christina and Baillie, Professor George
Authors: Engelhardt, B., Holze, J., Elliott, C., Baillie, G.S., Kschischo, M., and Fröhlich, H.
College/School:College of Medical Veterinary and Life Sciences > School of Cardiovascular & Metabolic Health
Journal Name:Mathematical Medicine and Biology
Publisher:Oxford University Press
ISSN (Online):1477-8602
Published Online:15 May 2017
Copyright Holders:Copyright © 2017 The Authors
First Published:First published in Mathematical Medicine and Biology 35(3): 279-297
Publisher Policy:Reproduced under a Creative Commons License

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