The Influence of Gene Expression Time Delays on Gierer–Meinhardt Pattern Formation Systems
Type
ArticleKAUST Grant Number
KUK-C1-013-04Date
2010-03-23Online Publication Date
2010-03-23Print Publication Date
2010-11Permanent link to this record
http://hdl.handle.net/10754/599921
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There are numerous examples of morphogen gradients controlling long range signalling in developmental and cellular systems. The prospect of two such interacting morphogens instigating long range self-organisation in biological systems via a Turing bifurcation has been explored, postulated, or implicated in the context of numerous developmental processes. However, modelling investigations of cellular systems typically neglect the influence of gene expression on such dynamics, even though transcription and translation are observed to be important in morphogenetic systems. In particular, the influence of gene expression on a large class of Turing bifurcation models, namely those with pure kinetics such as the Gierer-Meinhardt system, is unexplored. Our investigations demonstrate that the behaviour of the Gierer-Meinhardt model profoundly changes on the inclusion of gene expression dynamics and is sensitive to the sub-cellular details of gene expression. Features such as concentration blow up, morphogen oscillations and radical sensitivities to the duration of gene expression are observed and, at best, severely restrict the possible parameter spaces for feasible biological behaviour. These results also indicate that the behaviour of Turing pattern formation systems on the inclusion of gene expression time delays may provide a means of distinguishing between possible forms of interaction kinetics. Finally, this study also emphasises that sub-cellular and gene expression dynamics should not be simply neglected in models of long range biological pattern formation via morphogens. © 2010 Society for Mathematical Biology.Citation
Seirin Lee S, Gaffney EA, Monk NAM (2010) The Influence of Gene Expression Time Delays on Gierer–Meinhardt Pattern Formation Systems. Bull Math Biol 72: 2139–2160. Available: http://dx.doi.org/10.1007/s11538-010-9532-5.Sponsors
This publication is based on work supported in part by Award No. KUK-C1-013-04, made by King Abdullah University of Science and Technology (KAUST). SSL would like to thank Professor PK Maini and The Centre for Mathematical Biology for warm hospitality and a visiting position as well as gratefully acknowledging funding from the Japan Society for the Promotion of Science (JSPS Fellowship DC1).Publisher
Springer NatureJournal
Bulletin of Mathematical BiologyPubMed ID
20309645ae974a485f413a2113503eed53cd6c53
10.1007/s11538-010-9532-5
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