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Ultrasensitivity in Phosphorylation-Dephosphorylation Cycles with Little Substrate

Overview of attention for article published in PLoS Computational Biology, August 2013
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Title
Ultrasensitivity in Phosphorylation-Dephosphorylation Cycles with Little Substrate
Published in
PLoS Computational Biology, August 2013
DOI 10.1371/journal.pcbi.1003175
Pubmed ID
Authors

Bruno M. C. Martins, Peter S. Swain

Abstract

Cellular decision-making is driven by dynamic behaviours, such as the preparations for sunrise enabled by circadian rhythms and the choice of cell fates enabled by positive feedback. Such behaviours are often built upon ultrasensitive responses where a linear change in input generates a sigmoidal change in output. Phosphorylation-dephosphorylation cycles are one means to generate ultrasensitivity. Using bioinformatics, we show that in vivo levels of kinases and phosphatases frequently exceed the levels of their corresponding substrates in budding yeast. This result is in contrast to the conditions often required by zero-order ultrasensitivity, perhaps the most well known means for how such cycles become ultrasensitive. We therefore introduce a mechanism to generate ultrasensitivity when numbers of enzymes are higher than numbers of substrates. Our model combines distributive and non-distributive actions of the enzymes with two-stage binding and concerted allosteric transitions of the substrate. We use analytical and numerical methods to calculate the Hill number of the response. For a substrate with [Formula: see text] phosphosites, we find an upper bound of the Hill number of [Formula: see text], and so even systems with a single phosphosite can be ultrasensitive. Two-stage binding, where an enzyme must first bind to a binding site on the substrate before it can access the substrate's phosphosites, allows the enzymes to sequester the substrate. Such sequestration combined with competition for each phosphosite provides an intuitive explanation for the sigmoidal shifts in levels of phosphorylated substrate. Additionally, we find cases for which the response is not monotonic, but shows instead a peak at intermediate levels of input. Given its generality, we expect the mechanism described by our model to often underlay decision-making circuits in eukaryotic cells.

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Geographical breakdown

Country Count As %
Portugal 1 1%
United Kingdom 1 1%
Spain 1 1%
Japan 1 1%
United States 1 1%
Unknown 62 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 19 28%
Student > Ph. D. Student 16 24%
Professor 5 7%
Professor > Associate Professor 5 7%
Student > Master 3 4%
Other 7 10%
Unknown 12 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 23 34%
Biochemistry, Genetics and Molecular Biology 11 16%
Physics and Astronomy 7 10%
Engineering 3 4%
Chemistry 3 4%
Other 6 9%
Unknown 14 21%