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Regulation by competing: A hidden layer of gene regulatory networks

Quantitative understanding of biological regulation is essential for studying natural biosystems and for constructing synthetic systems. Current studies on gene regulation are used to build models under the assumption that gene regulators acting on a single or few targets. However, many regulators are actually shared between multiple target species with varying binding affinities, and target molecules often exist at different copy number. If the regulator is not in excess relative to target molecule pool, targets could cross talk with each other by competing for a limited pool of sharing regulators. Emerging examples suggest that such competing effects are wide spread in biosystems, including transcription factor binding, ribosome allocation, microRNA regulation, protein degradation, etc. We proposed a mathematical model to describe the common properties of these diverse competing regulatory systems, and implemented synthetic gene circuits to understand the quantitative behaviors of microRNA-target competing effects in human cell (1,2). Our work and several resent papers demonstrate that, molecular competing effects can couple the expression level of target molecules (3), introduce ultra-sensitivity to regulation dose-response curve (1,4), control temporal dynamics of gene expression (5), filter high frequency noises, and influence the stability of synthetic gene circuits (6). Systematic study of competitive regulation is essential for the precise control of synthetic biological systems.