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Revealing a two-loop transcriptional feedback mechanism in the cyanobacterial circadian clock

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Item Type:Article
Title:Revealing a two-loop transcriptional feedback mechanism in the cyanobacterial circadian clock
Creators Name:Hertel, S. and Brettschneider, C. and Axmann, I.M.
Abstract:Molecular genetic studies in the circadian model organism Synechococcus have revealed that the KaiC protein, the central component of the circadian clock in cyanobacteria, is involved in activation and repression of its own gene transcription. During 24 hours, KaiC hexamers run through different phospho-states during daytime. So far, it has remained unclear which phospho-state of KaiC promotes kaiBC expression and which opposes transcriptional activation. We systematically analyzed various combinations of positive and negative transcriptional feedback regulation by introducing a combined TTFL/PTO model consisting of our previous post-translational oscillator that considers all four phospho-states of KaiC and a transcriptional/translational feedback loop. Only a particular two-loop feedback mechanism out of 32 we have extensively tested is able to reproduce existing experimental observations, including the effects of knockout or overexpression of kai genes. Here, threonine and double phosphorylated KaiC hexamers activate and unphosphorylated KaiC hexamers suppress kaiBC transcription. Our model simulations suggest that the peak expression ratio of the positive and the negative component of kaiBC expression is the main factor for how the different two-loop feedback models respond to removal or to overexpression of kai genes. We discuss parallels between our proposed TTFL/PTO model and two-loop feedback structures found in the mammalian clock.
Keywords:Bacterial Gene Expression Regulation, Bacterial Proteins, Biological Models, Circadian Clocks, Circadian Rhythm Signaling Peptides and Proteins, Computational Biology, Computer Simulation, Cyanobacteria, Genetic Transcription, Mutation, Phosphorylation, Physiological Feedback
Source:PLoS Computational Biology
Publisher:Public Library of Science
Page Range:e1002966
Date:14 March 2013
Official Publication:https://doi.org/10.1371/journal.pcbi.1002966
PubMed:View item in PubMed

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