Mean-Independent Noise Control of Cell Fates via Intermediate States

• Published in: iScience Vol. 3; pp. 11 - 20
• Main Authors: Rackauckas, Christopher, Schilling, Thomas, Nie, Qing
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 25.05.2018; Elsevier
• Subjects: Bioinformatics; Developmental Biology; Systems Biology; Developmental Biology; Bioinformatics; Systems Biology
• ISSN: 2589-0042; 2589-0042
• DOI: 10.1016/j.isci.2018.04.002

Stochasticity affects accurate signal detection and robust generation of correct cell fates. Although many known regulatory mechanisms may reduce fluctuations in signals, most simultaneously influence their mean dynamics, leading to unfaithful cell fates. Through analysis and computation, we demonstrate that a reversible signaling mechanism acting through intermediate states can reduce noise while maintaining the mean. This mean-independent noise control (MINC) mechanism is investigated in the context of an intracellular binding protein that regulates retinoic acid (RA) signaling during zebrafish hindbrain development. By comparing our models with experimental data, we find that the MINC mechanism allows for sharp boundaries of gene expression without sacrificing boundary accuracy. In addition, this MINC mechanism can modulate noise to levels that we show are beneficial to spatial patterning through noise-induced cell fate switching. These results reveal a design principle that may be important for noise regulation in many systems that control cell fate determination. [Display omitted] •Mean-independent noise control allows noise attenuation without affecting the mean•Intermediate states enable such control through proportional coupling•This controls spatial gene expression noise without shifting boundary locations•Specific noise levels are required for successful downstream boundary sharpening Developmental Biology; Bioinformatics; Systems Biology