PUBLICATION

Mean-Independent Noise Control of Cell Fates via Intermediate States

Authors
Rackauckas, C., Schilling, T., Nie, Q.
ID
ZDB-PUB-181115-15
Date
2018
Source
iScience   3: 11-20 (Journal)
Registered Authors
Schilling, Tom
Keywords
Bioinformatics, Developmental Biology, Systems Biology
MeSH Terms
none
PubMed
30428314 Full text @ iScience
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.
Genes / Markers
Figures
Expression
Phenotype
Mutations / Transgenics
Human Disease / Model
Sequence Targeting Reagents
Fish
Antibodies
Orthology
Engineered Foreign Genes
Mapping