Mean-Independent Noise Control of Cell Fates via Intermediate States

Christopher Rackauckas; Thomas Schilling; Qing Nie

doi:10.1016/j.isci.2018.04.002

Mean-Independent Noise Control of Cell Fates via Intermediate States

iScience. 2018 May 25:3:11-20. doi: 10.1016/j.isci.2018.04.002. Epub 2018 Apr 11.

Authors

Christopher Rackauckas¹, Thomas Schilling², Qing Nie³

Affiliations

¹ Department of Mathematics, University of California, Irvine, Irvine, CA 92697, USA; Center for Complex Biological Systems, University of California, Irvine, Irvine, CA 92697, USA.
² Center for Complex Biological Systems, University of California, Irvine, Irvine, CA 92697, USA; Department of Developmental and Cell Biology, University of California, Irvine, Irvine, CA 92697, USA.
³ Department of Mathematics, University of California, Irvine, Irvine, CA 92697, USA; Center for Complex Biological Systems, University of California, Irvine, Irvine, CA 92697, USA; Department of Developmental and Cell Biology, University of California, Irvine, Irvine, CA 92697, USA. Electronic address: qnie@uci.edu.

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.

Keywords: Bioinformatics; Developmental Biology; Systems Biology.

Abstract

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