Spatial-Stochastic modelling of synthetic gene regulatory networks

Cicely K. Macnamara, Elaine I. Mitchell, Mark A. J. Chaplain (Lead / Corresponding author)

Research output: Contribution to journalArticle

Abstract

Transcription factors are important molecules which control the levels of mRNA and proteins within cells by modulating the process of transcription (the mechanism by which mRNA is produced within cells) and hence translation (the mechanism by which proteins are produced within cells). Transcription factors are part of a wider family of molecular interaction networks known as gene regulatory networks (GRNs) which play an important role in key cellular processes such as cell division and apoptosis (e.g. the p53-Mdm2, NFκB pathways). Transcription factors exert control over molecular levels through feedback mechanisms, with proteins binding to gene sites in the nucleus and either up-regulating or down-regulating production of mRNA. In many GRNs, there is a negative feedback in the network and the transcription rate is reduced. Typically, this leads to the mRNA and protein levels oscillating over time and also spatially between the nucleus and cytoplasm. When experimental data for such systems is analysed, it is observed to be noisy and in many cases the actual numbers of molecules involved are quite low. In order to model such systems accurately and connect with the data in a quantitative way, it is therefore necessary to adopt a stochastic approach as well as take into account the spatial aspect of the problem. In this paper, we extend previous work in the area by formulating and analysing stochastic spatio-temporal models of synthetic GRNs e.g. repressilators and activator-repressor systems.

Original languageEnglish
Pages (from-to)27-44
Number of pages18
JournalJournal of Theoretical Biology
Volume468
Early online date10 Feb 2019
DOIs
Publication statusPublished - 7 May 2019

Fingerprint

Synthetic Genes
synthetic genes
Spatial Modeling
Stochastic Modeling
Gene Regulatory Networks
Gene Regulatory Network
Messenger RNA
Transcription factors
transcription factors
Transcription Factor
Genes
Protein
Transcription Factors
Transcription
transcription (genetics)
Proteins
Nucleus
Cell
proteins
protein binding

Keywords

  • Activator-repressor systems
  • Repressilators
  • Spatial-stochastic modelling
  • Synthetic gene regulatory networks

Cite this

Macnamara, Cicely K. ; Mitchell, Elaine I. ; Chaplain, Mark A. J. / Spatial-Stochastic modelling of synthetic gene regulatory networks. In: Journal of Theoretical Biology. 2019 ; Vol. 468. pp. 27-44.
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Spatial-Stochastic modelling of synthetic gene regulatory networks. / Macnamara, Cicely K.; Mitchell, Elaine I.; Chaplain, Mark A. J. (Lead / Corresponding author).

In: Journal of Theoretical Biology, Vol. 468, 07.05.2019, p. 27-44.

Research output: Contribution to journalArticle

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