Literature DB >> 21184761

Spatio-temporal modelling of the Hes1 and p53-Mdm2 intracellular signalling pathways.

Marc Sturrock1, Alan J Terry, Dimitris P Xirodimas, Alastair M Thompson, Mark A J Chaplain.   

Abstract

The correct localisation of transcription factors is vitally important for the proper functioning of many intracellular signalling pathways. Experimental data has shown that many pathways exhibit oscillations in concentrations of the substances involved, both temporally and spatially. Negative feedback loops are important components of these oscillations, providing fine regulation for the factors involved. In this paper we consider mathematical models of two such pathways-Hes1 and p53-Mdm2. Building on previous mathematical modelling approaches, we derive systems of partial differential equations to capture the evolution in space and time of the variables in the Hes1 and p53-Mdm2 systems. Through computational simulations we show that our reaction-diffusion models are able to produce sustained oscillations both spatially and temporally, accurately reflecting experimental evidence and advancing previous models. The simulations of our models also allow us to calculate a diffusion coefficient range for the variables in each mRNA and protein system, as well as ranges for other key parameters of the models, where sustained oscillations are observed. Finally, by exploiting the explicitly spatial nature of the partial differential equations, we are also able to manipulate mathematically the spatial location of the ribosomes, thus controlling where the proteins are synthesized within the cytoplasm. The results of these simulations predict an optimal distance outside the nucleus where protein synthesis should take place in order to generate sustained oscillations. Using partial differential equation models, new information can be gained about the precise spatio-temporal dynamics of mRNA and proteins. The ability to determine spatial localisation of proteins within the cell is likely to yield fresh insight into a range of cellular diseases such as diabetes and cancer.
Copyright © 2010 Elsevier Ltd. All rights reserved.

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Year:  2010        PMID: 21184761     DOI: 10.1016/j.jtbi.2010.12.016

Source DB:  PubMed          Journal:  J Theor Biol        ISSN: 0022-5193            Impact factor:   2.691


  15 in total

1.  Mean field analysis of a spatial stochastic model of a gene regulatory network.

Authors:  M Sturrock; P J Murray; A Matzavinos; M A J Chaplain
Journal:  J Math Biol       Date:  2014-10-17       Impact factor: 2.259

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Authors:  Yu Xu; Hong Wang; Ruth Nussinov; Buyong Ma
Journal:  Proteomics       Date:  2013-03-18       Impact factor: 3.984

3.  The role of dimerisation and nuclear transport in the Hes1 gene regulatory network.

Authors:  Marc Sturrock; Andreas Hellander; Sahar Aldakheel; Linda Petzold; Mark A J Chaplain
Journal:  Bull Math Biol       Date:  2013-05-18       Impact factor: 1.758

4.  An investigation of spatial signal transduction in cellular networks.

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5.  The pharmacodynamics of the p53-Mdm2 targeting drug Nutlin: the role of gene-switching noise.

Authors:  Krzysztof Puszynski; Alberto Gandolfi; Alberto d'Onofrio
Journal:  PLoS Comput Biol       Date:  2014-12-11       Impact factor: 4.475

6.  Spatial stochastic modelling of the Hes1 gene regulatory network: intrinsic noise can explain heterogeneity in embryonic stem cell differentiation.

Authors:  Marc Sturrock; Andreas Hellander; Anastasios Matzavinos; Mark A J Chaplain
Journal:  J R Soc Interface       Date:  2013-01-16       Impact factor: 4.118

7.  Mechanisms that enhance sustainability of p53 pulses.

Authors:  Jae Kyoung Kim; Trachette L Jackson
Journal:  PLoS One       Date:  2013-06-03       Impact factor: 3.240

Review 8.  Reaction-diffusion systems for spatio-temporal intracellular protein networks: A beginner's guide with two examples.

Authors:  Ján Eliaš; Jean Clairambault
Journal:  Comput Struct Biotechnol J       Date:  2014-06-11       Impact factor: 7.271

9.  Insulin Signaling in Insulin Resistance States and Cancer: A Modeling Analysis.

Authors:  Alessandro Bertuzzi; Federica Conte; Geltrude Mingrone; Federico Papa; Serenella Salinari; Carmela Sinisgalli
Journal:  PLoS One       Date:  2016-05-05       Impact factor: 3.240

10.  A novel mathematical model of ATM/p53/NF- κB pathways points to the importance of the DDR switch-off mechanisms.

Authors:  Katarzyna Jonak; Monika Kurpas; Katarzyna Szoltysek; Patryk Janus; Agata Abramowicz; Krzysztof Puszynski
Journal:  BMC Syst Biol       Date:  2016-08-15
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