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Abstract Stochastic networks for the clock were identified by ensemble methods using genetic algorithms that captured the amplitude and period variation in single cell oscillators ofNeurosporacrassa. The genetic algorithms were at least an order of magnitude faster than ensemble methods using parallel tempering and appeared to provide a globally optimum solution from a random start in the initial guess of model parameters (i.e., rate constants and initial counts of molecules in a cell). The resulting goodness of fit$${x}^{2}$$ was roughly halved versus solutions produced by ensemble methods using parallel tempering, and the resulting$${x}^{2}$$ per data point was only$${\chi }^{2}/n$$ = 2,708.05/953 = 2.84. The fitted model ensemble was robust to variation in proxies for “cell size”. The fitted neutral models without cellular communication between single cells isolated by microfluidics provided evidence for onlyoneStochastic Resonance at one common level of stochastic intracellular noise across days from 6 to 36 h of light/dark (L/D) or in a D/D experiment. When the light-driven phase synchronization was strong as measured by the Kuramoto (K), there was degradation in the single cell oscillations away from the stochastic resonance. The rate constants for the stochastic clock network are consistent with those determined on a macroscopic scale of 107cells.
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This content will become publicly available on January 14, 2027
Origin of the clock in Neurospora crassa
We examine the collective behavior of single cells in microbial systems to provide insights into the origin of the biological clock. Microfluidics has opened a window onto how single cells can synchronize their behavior. Four hypotheses are proposed to explain the origin of the clock from the synchronized behavior of single cells. These hypotheses depend on the presence or absence of a communication mechanism between the clocks in single cells and the presence or absence of a stochastic component in the clock mechanism. To test these models, we integrate physical models for the behavior of the clocks in single cells or filaments with new approaches to measuring clocks in single cells. As an example, we provide evidence for a quorum-sensing signal both with microfluidics experiments on single cells and with continuousin vivometabolism NMR (CIVM-NMR). We also provide evidence for the stochastic component in clocks of single cells. Throughout this study, ensemble methods from statistical physics are used to characterize the clock at both the single-cell level and the macroscopic scale of 106cells.
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- Award ID(s):
- 2503759
- PAR ID:
- 10659448
- Author(s) / Creator(s):
- ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; more »
- Editor(s):
- Ciofani, G
- Publisher / Repository:
- Frontiers in Molecular Biosciences
- Date Published:
- Journal Name:
- Frontiers in Molecular Biosciences
- Volume:
- 12
- ISSN:
- 2296-889X
- Subject(s) / Keyword(s):
- biological clock ensemble methods nanotechnology stochastic resonance stochastic coherence transcriptional bursting
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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