Noise processing by microRNA-mediated circuits: The Incoherent Feed-Forward Loop, revisited

Area of Science:

• Systems Biology
• Molecular Biology
• Genetics

Background:

• Gene expression exhibits intrinsic stochasticity, which is typically buffered by post-transcriptional regulation in higher eukaryotes.
• MicroRNAs (miRNAs) are implicated in noise buffering within genetic regulatory networks, a function supported by in vitro and in silico studies.
• Transcriptional bursting can compromise miRNA-mediated noise reduction in simple regulatory structures.

Purpose of the Study:

• To investigate the noise-buffering capacity of the miRNA-mediated Incoherent Feed Forward Loop (IFFL) under conditions of intermittent transcriptional activity.
• To analyze the impact of transcriptional bursting on the IFFL's ability to control static protein noise.
• To compare the performance of the IFFL with other regulatory architectures in managing gene expression noise.

Main Methods:

• Stochastic simulations were employed to model gene expression dynamics.
• Analytical calculations, utilizing van Kampen's expansion, were used to validate simulation results.
• The noise-buffering capacity of the miRNA-mediated IFFL was assessed, considering pulsatile transcriptional inputs.

Main Results:

• Transcriptional bursting significantly alters the IFFL's effectiveness in controlling static protein noise.
• Direct transcriptional regulation was found to outperform the IFFL in noise reduction across a wide range of kinetic parameters.
• The study highlights that under pulsatile conditions, dynamical noise aspects and information processing may be more critical than static noise reduction.

Conclusions:

• The miRNA-mediated IFFL's noise-buffering capacity is substantially reduced by transcriptional bursting.
• For pulsatile gene expression, direct transcriptional regulation offers superior static noise control compared to the IFFL.
• The findings suggest a shift in focus from static noise reduction to dynamic noise properties and information processing for evaluating regulatory elements under fluctuating conditions.