Internal noise-sustained circadian rhythms in a Drosophila model.
Circadian rhythmic processes, mainly regulated by gene expression at the molecular level, have inherent stochasticity. Their robustness or resistance to internal noise has been extensively investigated by most of the previous studies. This work focuses on the constructive roles of internal noise in a reduced Drosophila model, which incorporates negative and positive feedback loops, each with a time delay. It is shown that internal noise sustains reliable oscillations with periods close to 24 h in a region of parameter space, where the deterministic kinetics would evolve to a stable steady state. The amplitudes of noise-sustained oscillations are significantly affected by the variation of internal noise level, and the best performance of the oscillations could be found at an optimal noise intensity, indicating the occurrence of intrinsic coherence resonance. In the oscillatory region of the deterministic model, the coherence of noisy circadian oscillations is suppressed by internal noise, while the period remains nearly constant over a large range of noise intensity, demonstrating robustness of the Drosophila model for circadian rhythms to intrinsic noise. In addition, the effects of time delay in the positive feedback on the oscillations are also investigated. It is found that the time delay could efficiently tune the performance of the noise-sustained oscillations. These results might aid understanding of the exploitation of intracellular noise in biochemical and genetic regulatory systems.
Li
Qianshu
Q
School of Chemical Engineering and the Environment, Beijing Institute of Technology, Beijing, China. qsli@bit
Lang
Xiufeng
X
D000818:Animals; D001703:Biophysics / Q000379:methods*; D002468:Cell Physiological Phenomena; D002940:Circadian Rhythm; D004331:Drosophila melanogaster; D007700:Kinetics; D008954:Models, Biological; D015233:Models, Statistical; D009991:Oscillometry; D015203:Reproducibility of Results; D013269:Stochastic Processes; D013997:Time Factors