MicroRNAs as dynamic processors: from thresholding to temporal decoding

MicroRNAs are central regulators of gene expression. Traditionally viewed as static repressors of protein output, their regulatory role is increasingly recognized as inherently dynamic. In living systems, gene regulation unfolds far from equilibrium, where signals fluctuate over time, molecular abundances vary stochastically, and cellular decisions depend on temporal context. Within this framework, microRNA-mediated regulation emerges not simply as a buffering layer, but as an active component of dynamic information processing. In this review, we present a dynamical perspective on microRNA-mediated regulation. We first discuss how the stoichiometric nature of microRNA-target interactions gives rise to ultrasensitive and threshold-like responses, and how these nonlinear properties extend beyond steady-state repression to shape temporal and stochastic regulation. We examine how sequestration-based mechanisms can support frequency-dependent responses, selective decoding of time-varying signals, and context-dependent modulation of gene expression noise. Together, these observations support a dynamical perspective in which microRNAs contribute to the processing, filtering, and integration of regulatory information across multiple timescales.