Year: 2018
Type: article
Abstract: 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.
Source: iScience
Institution: University of California, Irvine
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,240
Awards: G1885747215, G1902661011, Collaborative Research: Early Mammalian Embryo Development: Stochastic Modeling and Experiments, G2476227316, Differentiation and Stratification during Development: A Joint Computational and Experimental Investigation, G3100750127, Graduate Research Fellowship Program (GRFP), G4593182465, Systems Biology of Morphogeneisis and Spatial Information Flow, G5511088259, G5780912566, Stochastic Dynamics and Noise Control in Patterning Systems, G6575219130, G7038253247, G777608911, G784608047, G8072079600, G8321196933, Mathematical, Computational and Systems Biology, G9000039775
OpenAlex ID: W2797319337