A mechanism for robust circadian timekeeping via stoichiometric balance

Molecular Systems Biology

Jae Kyoung Kim¹ 

[1] Department of Mathematics, University of Michigan, Ann Arbor, MI, USA

关键词: biological clocks;    circadian rhythms;    gene regulatory networks;    mathematical model;    robustness;   

DOI  :  10.1038/msb.2012.62

来源: Wiley

【 摘 要 】

Abstract

Circadian (∼24 h) timekeeping is essential for the lives of many organisms. To understand the biochemical mechanisms of this timekeeping, we have developed a detailed mathematical model of the mammalian circadian clock. Our model can accurately predict diverse experimental data including the phenotypes of mutations or knockdown of clock genes as well as the time courses and relative expression of clock transcripts and proteins. Using this model, we show how a universal motif of circadian timekeeping, where repressors tightly bind activators rather than directly binding to DNA, can generate oscillations when activators and repressors are in stoichiometric balance. Furthermore, we find that an additional slow negative feedback loop preserves this stoichiometric balance and maintains timekeeping with a fixed period. The role of this mechanism in generating robust rhythms is validated by analysis of a simple and general model and a previous model of the Drosophila circadian clock. We propose a double-negative feedback loop design for biological clocks whose period needs to be tightly regulated even with large changes in gene dosage.

Synopsis

An accurate mathematical model of the mammalian circadian clock provides novel insights into the mechanisms that generate 24-h rhythms. A double-negative feedback loop design is proposed for biological clocks whose period needs to be tightly regulated.

• A 1–1 stoichiometric balance and tight binding between activators (PER–CRY) and repressors (BMAL1–CLOCK/NPAS2) is required for sustained rhythmicity.
• Stoichiometry is balanced by an additional negative feedback loop consisting of a stable activator.
• Our detailed model can explain more experimental data than previous models.
• Mathematical analysis of a simple model supports our claims.

【 授权许可】

CC BY-NC-SA   
Copyright © 2012 EMBO and Macmillan Publishers Limited

Creative Commons Attribution License, which permits distribution, and reproduction in any medium, provided the original author and source are credited. This license does not permit commercial exploitation without specific permission.