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Stochastic Noise and Synchronisation during Dictyostelium Aggregation Make cAMP Oscillations Robust

Overview of attention for article published in PLoS Computational Biology, November 2007
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Title
Stochastic Noise and Synchronisation during Dictyostelium Aggregation Make cAMP Oscillations Robust
Published in
PLoS Computational Biology, November 2007
DOI 10.1371/journal.pcbi.0030218
Pubmed ID
Authors

Jongrae Kim, Pat Heslop-Harrison, Ian Postlethwaite, Declan G Bates

Abstract

Stable and robust oscillations in the concentration of adenosine 3', 5'-cyclic monophosphate (cAMP) are observed during the aggregation phase of starvation-induced development in Dictyostelium discoideum. In this paper we use mathematical modelling together with ideas from robust control theory to identify two factors which appear to make crucial contributions to ensuring the robustness of these oscillations. Firstly, we show that stochastic fluctuations in the molecular interactions play an important role in preserving stable oscillations in the face of variations in the kinetics of the intracellular network. Secondly, we show that synchronisation of the aggregating cells through the diffusion of extracellular cAMP is a key factor in ensuring robustness of the oscillatory waves of cAMP observed in Dictyostelium cell cultures to cell-to-cell variations. A striking and quite general implication of the results is that the robustness analysis of models of oscillating biomolecular networks (circadian clocks, Ca(2+) oscillations, etc.) can only be done reliably by using stochastic simulations, even in the case where molecular concentrations are very high.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 62 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 4 6%
Japan 1 2%
Germany 1 2%
Unknown 56 90%

Demographic breakdown

Readers by professional status Count As %
Researcher 17 27%
Student > Ph. D. Student 12 19%
Professor > Associate Professor 8 13%
Other 8 13%
Student > Master 4 6%
Other 8 13%
Unknown 5 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 20 32%
Biochemistry, Genetics and Molecular Biology 12 19%
Physics and Astronomy 8 13%
Engineering 4 6%
Computer Science 3 5%
Other 7 11%
Unknown 8 13%