Bayesian modeling reveals metabolite‐dependent ultrasensitivity in the cyanobacterial circadian clock
Abstract: 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.
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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Online-Ressource
- Sprache
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Englisch
- Erschienen in
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Bayesian modeling reveals metabolite‐dependent ultrasensitivity in the cyanobacterial circadian clock ; volume:16 ; number:6 ; year:2020 ; extent:23
Molecular systems biology ; 16, Heft 6 (2020) (gesamt 23)
- Urheber
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Hong, Lu
Lavrentovich, Danylo O.
Chavan, Archana
Leypunskiy, Eugene
Li, Eileen
Matthews, Charles
LiWang, Andy
Rust, Michael J.
Dinner, Aaron R.
- DOI
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10.15252/msb.20199355
- URN
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urn:nbn:de:101:1-2022062410061394543475
- Rechteinformation
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
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15.08.2025, 07:24 MESZ
Datenpartner
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Hong, Lu
- Lavrentovich, Danylo O.
- Chavan, Archana
- Leypunskiy, Eugene
- Li, Eileen
- Matthews, Charles
- LiWang, Andy
- Rust, Michael J.
- Dinner, Aaron R.
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