Spatio-temporal models of synthetic genetic oscillators
Signal transduction pathways play a major role in many important aspects of cellular function e.g. cell division, apoptosis. One important class of signal transduction pathways is gene regulatory networks (GRNs). In many GRNs, proteins bind to gene sites in the nucleus thereby altering the transcrip...
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AIMS Press
2017-01-01
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| Series: | Mathematical Biosciences and Engineering |
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| Online Access: | https://www.aimspress.com/article/doi/10.3934/mbe.2017016 |
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| author | Cicely K. Macnamara Mark A. J. Chaplain |
| author_facet | Cicely K. Macnamara Mark A. J. Chaplain |
| author_sort | Cicely K. Macnamara |
| collection | DOAJ |
| description | Signal transduction pathways play a major role in many important aspects of cellular function e.g. cell division, apoptosis. One important class of signal transduction pathways is gene regulatory networks (GRNs). In many GRNs, proteins bind to gene sites in the nucleus thereby altering the transcription rate. Such proteins are known as transcription factors. If the binding reduces the transcription rate there is a negative feedback leading to oscillatory behaviour in mRNA and protein levels, both spatially (e.g. by observing fluorescently labelled molecules in single cells) and temporally (e.g. by observing protein/mRNA levels over time). Recent computational modelling has demonstrated that spatial movement of the molecules is a vital component of GRNs and may cause the oscillations. These numerical findings have subsequently been proved rigorously i.e. the diffusion coefficient of the protein/mRNA acts as a bifurcation parameter and gives rise to a Hopf bifurcation. In this paper we first present a model of the canonical GRN (the Hes1 protein) and show the effect of varying the spatial location of gene and protein production sites on the oscillations. We then extend the approach to examine spatio-temporal models of synthetic gene regulatory networks e.g. n-gene repressilators and activator-repressor systems. |
| format | Article |
| id | doaj-art-73b2fea57cff4018b250352d331885de |
| institution | Kabale University |
| issn | 1551-0018 |
| language | English |
| publishDate | 2017-01-01 |
| publisher | AIMS Press |
| record_format | Article |
| series | Mathematical Biosciences and Engineering |
| spelling | doaj-art-73b2fea57cff4018b250352d331885de2025-01-24T02:39:32ZengAIMS PressMathematical Biosciences and Engineering1551-00182017-01-0114124926210.3934/mbe.2017016Spatio-temporal models of synthetic genetic oscillatorsCicely K. Macnamara0Mark A. J. Chaplain1School of Mathematics and Statistics, Mathematical Institute, North Haugh, University of St Andrews, St Andrews KY16 9SS, ScotlandSchool of Mathematics and Statistics, Mathematical Institute, North Haugh, University of St Andrews, St Andrews KY16 9SS, ScotlandSignal transduction pathways play a major role in many important aspects of cellular function e.g. cell division, apoptosis. One important class of signal transduction pathways is gene regulatory networks (GRNs). In many GRNs, proteins bind to gene sites in the nucleus thereby altering the transcription rate. Such proteins are known as transcription factors. If the binding reduces the transcription rate there is a negative feedback leading to oscillatory behaviour in mRNA and protein levels, both spatially (e.g. by observing fluorescently labelled molecules in single cells) and temporally (e.g. by observing protein/mRNA levels over time). Recent computational modelling has demonstrated that spatial movement of the molecules is a vital component of GRNs and may cause the oscillations. These numerical findings have subsequently been proved rigorously i.e. the diffusion coefficient of the protein/mRNA acts as a bifurcation parameter and gives rise to a Hopf bifurcation. In this paper we first present a model of the canonical GRN (the Hes1 protein) and show the effect of varying the spatial location of gene and protein production sites on the oscillations. We then extend the approach to examine spatio-temporal models of synthetic gene regulatory networks e.g. n-gene repressilators and activator-repressor systems.https://www.aimspress.com/article/doi/10.3934/mbe.2017016gene regulatory networksdiffusion-driven oscillationssynthetic gene networksrepressilatorspositive-negative feedback |
| spellingShingle | Cicely K. Macnamara Mark A. J. Chaplain Spatio-temporal models of synthetic genetic oscillators Mathematical Biosciences and Engineering gene regulatory networks diffusion-driven oscillations synthetic gene networks repressilators positive-negative feedback |
| title | Spatio-temporal models of synthetic genetic oscillators |
| title_full | Spatio-temporal models of synthetic genetic oscillators |
| title_fullStr | Spatio-temporal models of synthetic genetic oscillators |
| title_full_unstemmed | Spatio-temporal models of synthetic genetic oscillators |
| title_short | Spatio-temporal models of synthetic genetic oscillators |
| title_sort | spatio temporal models of synthetic genetic oscillators |
| topic | gene regulatory networks diffusion-driven oscillations synthetic gene networks repressilators positive-negative feedback |
| url | https://www.aimspress.com/article/doi/10.3934/mbe.2017016 |
| work_keys_str_mv | AT cicelykmacnamara spatiotemporalmodelsofsyntheticgeneticoscillators AT markajchaplain spatiotemporalmodelsofsyntheticgeneticoscillators |