期刊
MOLECULAR SYSTEMS BIOLOGY
卷 16, 期 6, 页码 -出版社
WILEY
DOI: 10.15252/msb.20199355
关键词
Bayes factor; kinetic modeling; Markov chain Monte Carlo; robustness; substrate competition
资金
- National Science Foundation [MCB-1953402]
- National Institutes of Health [GM107369, GM107521, GM135382, EY025957]
- Department of Energy Office of Advanced Scientific Computing Research [DE-AC02-06CH11347, DE-SC0014205]
- Howard Hughes Medical Institute-Simons Foundation Faculty Scholarship
- Center for Cellular and Biomolecular Machines at University of California, Merced (NSF) [HRD-1547848]
- NSF [ACI-1548562]
- U.S. Department of Energy (DOE) [DE-SC0014205] Funding Source: U.S. Department of Energy (DOE)
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 inSynechococcus elongatushas 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 reconstitutedin 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.
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