Optimizing periodicity and polymodality in noise-induced genetic oscillators.

Area of Science:

• Systems Biology
• Molecular Biology
• Biophysics

Background:

• Cellular functions rely on rhythmic biological processes organized into self-repeating cascades.
• Some periodic biological processes, like cell cycles, show irregularities such as period skipping, leading to multimodal cycle length distributions.
• Molecular noise stabilizing a Hopf-unstable state is a proposed mechanism for this quantized behavior.

Purpose of the Study:

• To investigate the effect of varying noise levels on an excitable activator-repressor genetic circuit.
• To explore how molecular noise influences the regularity and periodicity patterns in biological systems.

Main Methods:

• Utilized a model system: an excitable activator-repressor genetic circuit.
• Simulated and analyzed the effects of different levels of molecular noise on the circuit's behavior.
• Quantified cycle regularity and the multimodal nature of cycle lengths.

Main Results:

• An optimal noise level was found to enhance the regularity (coherence) of the cycles, demonstrating coherence resonance.
• Similar optimal noise levels were observed to optimize the multimodal distribution of cycle lengths.
• The study confirmed noise-induced stabilization of a Hopf-unstable state.

Conclusions:

• Molecular noise plays a crucial role in conferring robustness to biological rhythms.
• Within a minimal gene regulatory motif, molecular noise can robustly generate polymodal patterns of periodicity.
• This work provides insights into how noise contributes to the precise temporal organization of cellular processes.