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Bayesian modeling reveals metabolite‐dependent ultrasensitivity in the cyanobacterial circadian clock
Mathematical models can enable a predictive understanding of mechanism in cell biology by quantitatively describing complex networks of interactions, but such models are often poorly constrained by available data. Owing to its relative biochemical simplicity, the core circadian oscillator in Synecho...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7271899/ https://www.ncbi.nlm.nih.gov/pubmed/32496641 http://dx.doi.org/10.15252/msb.20199355 |
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author | Hong, Lu Lavrentovich, Danylo O Chavan, Archana Leypunskiy, Eugene Li, Eileen Matthews, Charles LiWang, Andy Rust, Michael J Dinner, Aaron R |
author_facet | Hong, Lu Lavrentovich, Danylo O Chavan, Archana Leypunskiy, Eugene Li, Eileen Matthews, Charles LiWang, Andy Rust, Michael J Dinner, Aaron R |
author_sort | Hong, Lu |
collection | PubMed |
description | Mathematical models can enable a predictive understanding of mechanism in cell biology by quantitatively describing complex networks of interactions, but such models are often poorly constrained by available data. Owing to its relative biochemical simplicity, the core circadian oscillator in Synechococcus elongatus has become a prototypical system for studying how collective dynamics emerge from molecular interactions. The oscillator consists of only three proteins, KaiA, KaiB, and KaiC, and near‐24‐h cycles of KaiC phosphorylation can be reconstituted in vitro. Here, we formulate a molecularly detailed but mechanistically naive model of the KaiA—KaiC subsystem and fit it directly to experimental data within a Bayesian parameter estimation framework. Analysis of the fits consistently reveals an ultrasensitive response for KaiC phosphorylation as a function of KaiA concentration, which we confirm experimentally. This ultrasensitivity primarily results from the differential affinity of KaiA for competing nucleotide‐bound states of KaiC. We argue that the ultrasensitive stimulus–response relation likely plays an important role in metabolic compensation by suppressing premature phosphorylation at nighttime. |
format | Online Article Text |
id | pubmed-7271899 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-72718992020-06-05 Bayesian modeling reveals metabolite‐dependent ultrasensitivity in the cyanobacterial circadian clock Hong, Lu Lavrentovich, Danylo O Chavan, Archana Leypunskiy, Eugene Li, Eileen Matthews, Charles LiWang, Andy Rust, Michael J Dinner, Aaron R Mol Syst Biol Articles Mathematical models can enable a predictive understanding of mechanism in cell biology by quantitatively describing complex networks of interactions, but such models are often poorly constrained by available data. Owing to its relative biochemical simplicity, the core circadian oscillator in Synechococcus elongatus has become a prototypical system for studying how collective dynamics emerge from molecular interactions. The oscillator consists of only three proteins, KaiA, KaiB, and KaiC, and near‐24‐h cycles of KaiC phosphorylation can be reconstituted in vitro. Here, we formulate a molecularly detailed but mechanistically naive model of the KaiA—KaiC subsystem and fit it directly to experimental data within a Bayesian parameter estimation framework. Analysis of the fits consistently reveals an ultrasensitive response for KaiC phosphorylation as a function of KaiA concentration, which we confirm experimentally. This ultrasensitivity primarily results from the differential affinity of KaiA for competing nucleotide‐bound states of KaiC. We argue that the ultrasensitive stimulus–response relation likely plays an important role in metabolic compensation by suppressing premature phosphorylation at nighttime. John Wiley and Sons Inc. 2020-06-04 /pmc/articles/PMC7271899/ /pubmed/32496641 http://dx.doi.org/10.15252/msb.20199355 Text en © 2020 The Authors. Published under the terms of the CC BY 4.0 license This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Articles Hong, Lu Lavrentovich, Danylo O Chavan, Archana Leypunskiy, Eugene Li, Eileen Matthews, Charles LiWang, Andy Rust, Michael J Dinner, Aaron R Bayesian modeling reveals metabolite‐dependent ultrasensitivity in the cyanobacterial circadian clock |
title | Bayesian modeling reveals metabolite‐dependent ultrasensitivity in the cyanobacterial circadian clock |
title_full | Bayesian modeling reveals metabolite‐dependent ultrasensitivity in the cyanobacterial circadian clock |
title_fullStr | Bayesian modeling reveals metabolite‐dependent ultrasensitivity in the cyanobacterial circadian clock |
title_full_unstemmed | Bayesian modeling reveals metabolite‐dependent ultrasensitivity in the cyanobacterial circadian clock |
title_short | Bayesian modeling reveals metabolite‐dependent ultrasensitivity in the cyanobacterial circadian clock |
title_sort | bayesian modeling reveals metabolite‐dependent ultrasensitivity in the cyanobacterial circadian clock |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7271899/ https://www.ncbi.nlm.nih.gov/pubmed/32496641 http://dx.doi.org/10.15252/msb.20199355 |
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