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The robust ticking of a circadian clock David Zwicker, Jeroen van Zon,David Lubensky, Pim Altena, Pieter Rein ten Wolde Beijing, July 27, 2010 Synechococcus.

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Presentation on theme: "The robust ticking of a circadian clock David Zwicker, Jeroen van Zon,David Lubensky, Pim Altena, Pieter Rein ten Wolde Beijing, July 27, 2010 Synechococcus."— Presentation transcript:

1 The robust ticking of a circadian clock David Zwicker, Jeroen van Zon,David Lubensky, Pim Altena, Pieter Rein ten Wolde Beijing, July 27, 2010 Synechococcus Elongatus

2 Introduction: circadian rhythms  In general, circadian rhythms are: Free running ~24 hour oscillations Entrained to light

3 Circadian rhythms are very robust  Circadian clocks are extremely stable  higher organisms: cell-cell interactions  clock cyanobacteria stable at single cell level Mihalcescu, Hsing, Leibler, Nature (2004) Correlation time: 166 days!

4 Key questions:  How does the clock work?  How can it be so stable? Clock cyanobacterium S. elongatus ideal model system

5 Circadian rhythms: oscillations gene expression Three genes crucial: kaiA, kaiB, kaiC kaiBC forms an operon Expression kaiBC oscillates Continuous overexpression KaiC represses kaiBC Temporal overexpression KaiC resets phase Transcription-translation cycle (TTC)! kaiBC C C C C Golden, Johnson, Kondo, Science (1998)

6 Circadian rhythms: oscillations protein modification Protein phosphorylation cycle (PPC)! KaiC is hexamer with two phosphorylation sites per monomer In the dark: no gene expression, yet oscillations of phosphorylation level! Kondo lab, Science (2005A)

7 KaiC circadian oscillations in the test tube Kondo lab, Science (2005B) Test tube with KaiA, KaiB, KaiC and ATP (and water): oscillations! Is the PPC the principal pacemaker?

8 Oscillations of gene expression without oscillations of phosphorylation level TTC exists without a PPC! Is the TTC perhaps the pacemaker after all? Kondo lab, Genes & Development (2008) phosphorylation gene expression

9 Key question: Why does the system have a PPC and a TTC?

10 Overview PPC in vitro PPC in vivo TTC in vivo PPC + TTC

11 Overview PPC in vitro PPC in vivo TTC in vivo PPC + TTC

12 Overview models for PPC 1.Monomer shuffling: Emberly & Wingreen (PRL, 2006); Yoda, Eguchi,Terrada, Sasai (PLCB, 2007); Mori et al. (PB, 2007); 2.Differential affinity or sequestration Van Zon, Lubensky, Altena, Ten Wolde (PNAS, 2007); Clodong et al. (MSB, 2007); Rust et al. (Science 2007); For overview PPC models, see Markson & O’Shea (FEBS Lett, 2009)

13 Roadmap to working PPC model 1.Individual KaiC hexamers phosphorylate and dephosphorylate in a cyclical manner 2.Action of KaiA and KaiB synchronizes KaiC phosphorylation cycles by differential affinity

14 Allosteric cycle in KaiC phosphorylation ADP ATP  The subunits of a KaiC hexamer can exist in two conformational states, active and inactive  All subunits switch conformation collectively (MWC model)  ATP/ADP binding to subunits stabilizes the active state  Subunits with ATP bound become phosphorylated  Phosphorylated subunits are preferably in the inactive state unphosphorylated phosphorylated

15 Allosteric cycle in KaiC phosphorylation ADP ATP Fast ATP/ADP binding and unbinding: Partition function hexamer in state : Free energy of hexamer in state :

16 Allosteric cycle: thermodynamics ADP ATP Free energy of hexamers: Active Inactive

17 Allosteric cycle: thermodynamics ADP ATP Free energy system including ATP hydrolysis:

18 Allosteric cycle: flipping kinetics ADP ATP Nucleotide binding Conformational transition Flipping rate depends exponentially on degree of phosphorylation! p = 3

19 Allosteric cycle in KaiC phosphorylation No macroscopic oscillations due to lack of synchronization between the cycle of individual KaiC hexamers! Conformational transition

20 Synchronization by differential affinity: a toy model  KaiA stimulates phosphorylation of active KaiC  [KaiA] is smaller than [KaiC]  KaiA binds with differential affinity: it binds most strongly to less phosphorylated, active KaiC

21 Synchronization by differential affinity: a toy model Solve set of ODEs

22 Synchronization by differential affinity: a toy model KaiA binds and stimulates the laggards!

23 Full model Kai system: KaiC + KaiA KaiA + KaiC Kageyama et al. Mol. Cell 2006  KaiA stimulates phosphorylation of active KaiC  Binding of KaiA stabilizes active KaiC

24 Full model Kai system: KaiC + KaiB  KaiB does not stimulate phosphorylation  KaiB stabilizes inactive KaiC by binding it, restoring the cycle Xu et al. EMBO J. (2003) KaiC KaiC+KaiB

25 Full model: KaiC + KaiA + KaiB Nakajima et al. Science 2005  KaiB-KaiC binds to and sequesters KaiA, leading to another form of differential affinity

26 Phase portrait Changing KaiAChanging KaiB Experiment: Kageyama et al. Mol. Cell 2006 Model

27 Conclusions deterministic PPC model  Oscillations over large range of KaiA and KaiB concentrations  Reproduces experiments on subsets of Kai proteins  Robustness against variations in parameters: temperature compensation (not shown)  Our model makes several testable predictions J. S. van Zon, D. K. Lubensky, P. R. H. Altena, P. R. ten Wolde, PNAS 107, 7420 (2007) http://www.arxiv.org/abs/q-bio.MN/0703009

28 PPC in vitro: robustness to noise PPC is highly robust against noise!

29 PPC in vivo: PPC plus constitutive gene expression PPC in vitro PPC in vivo TTC in vivo PPC + TTC

30 PPC in vivo: PPC plus constitutive gene expression PPC not robust against variations growth rate!

31 PPC in vivo: PPC plus constitutive gene expression High growth rate: phosphorylation level new KaiC cannot catch up before degradation.

32 PPC plus TTC PPC in vitro PPC in vivo TTC in vivo PPC + TTC

33 PPC plus TTC TTC+PPC highly intertwined System differs from conventional coupled phase oscillators

34 PPC plus TTC: robustness PPC plus TTC highly robust.

35 TTC-only model PPC in vitro PPC in vivo TTC in vivo PPC + TTC

36 Comparison performance Only PPC+TTC robust over full range growth rates!

37 PPC - TTC: origin enhanced stability High copy number PPC Modification leads to delay Sharp threshold crossings enhances robustness to noise

38 Conclusions and outlook  Both TTC plus PPC are needed for robustness against variations in growth rate  Mechanism follows from simple argument on comparison protein decay timescale with oscillation period  Also higher organisms employ protein modification  Test by putting system in E.coli? http://www.arxiv.org/abs/q-bio.MN/1004.2821


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