Design principles for enhancing phase sensitivity and suppressing phase fluctuations simultaneously in biochemical oscillatory systems

Fei, Chenyi; Cao, Yuansheng; Ouyang, Qi; Tu, Yuhai

doi:10.1038/s41467-018-03826-4

Cited by 46 publications

(43 citation statements)

References 52 publications

(52 reference statements)

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“…We use a reversible Brusselator model 30 , 35 – 37 with dynamics governed by the reaction equations: where { A , B , C } are external chemical baths with fixed concentrations { a , b , c }, and all the reactions occur in a volume V (Fig. 2 a).…”

Section: Resultsmentioning

confidence: 99%

Irreversibility in dynamical phases and transitions

2021

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Living and non-living active matter consumes energy at the microscopic scale to drive emergent, macroscopic behavior including traveling waves and coherent oscillations. Recent work has characterized non-equilibrium systems by their total energy dissipation, but little has been said about how dissipation manifests in distinct spatiotemporal patterns. We introduce a measure of irreversibility we term the entropy production factor to quantify how time reversal symmetry is broken in field theories across scales. We use this scalar, dimensionless function to characterize a dynamical phase transition in simulations of the Brusselator, a prototypical biochemically motivated non-linear oscillator. We measure the total energetic cost of establishing synchronized biochemical oscillations while simultaneously quantifying the distribution of irreversibility across spatiotemporal frequencies.

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Section: Resultsmentioning

confidence: 99%

Irreversibility in dynamical phases and transitions

2021

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“…Interface 16: 20190098 biological function, placing an independent set of constraints on the system's architecture [27,30]. Entrainment efficiency has recently been shown to increase with dissipation rate in some models even when the free-running precision has saturated, providing an impetus for increasing the entropy production per cycle beyond what is required to achieve N ¼ N eff [31]. Acknowledgements.…”

Section: Discussionmentioning

confidence: 99%

The thermodynamic uncertainty relation in biochemical oscillations

Marsland

Cui

Horowitz

2019

J. R. Soc. Interface.

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Living systems regulate many aspects of their behaviour through periodic oscillations of molecular concentrations, which function as ‘biochemical clocks.’ The chemical reactions that drive these clocks are intrinsically stochastic at the molecular level, so that the duration of a full oscillation cycle is subject to random fluctuations. Their success in carrying out their biological function is thought to depend on the degree to which these fluctuations in the cycle period can be suppressed. Biochemical oscillators also require a constant supply of free energy in order to break detailed balance and maintain their cyclic dynamics. For a given free energy budget, the recently discovered ‘thermodynamic uncertainty relation’ yields the magnitude of period fluctuations in the most precise conceivable free-running clock. In this paper, we show that computational models of real biochemical clocks severely underperform this optimum, with fluctuations several orders of magnitude larger than the theoretical minimum. We argue that this suboptimal performance is due to the small number of internal states per molecule in these models, combined with the high level of thermodynamic force required to maintain the system in the oscillatory phase. We introduce a new model with a tunable number of internal states per molecule and confirm that it approaches the optimal precision as this number increases.

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“…The phase variance and the sensitivity are common measures and were used in Refs. [40][41][42] to study their tradeoff relation. However, an explicit inequality between the two quantities has not been reported yet.…”

Section: Example 2: Limit Cycle Oscillatormentioning

confidence: 99%

Uncertainty relations in stochastic processes: An information inequality approach

Hasegawa

2019

Phys. Rev. E

117

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The thermodynamic uncertainty relation is an inequality stating that it is impossible to attain higher precision than the bound defined by entropy production. In statistical inference theory, information inequalities assert that it is infeasible for any estimator to achieve an error smaller than the prescribed bound. Inspired by the similarity between the thermodynamic uncertainty relation and the information inequalities, we apply the latter to systems described by Langevin equations and derive the bound for the fluctuation of thermodynamic quantities. When applying the Cramér-Rao inequality, the obtained inequality reduces to the fluctuation-response inequality. We find that the thermodynamic uncertainty relation is a particular case of the Cramér-Rao inequality, in which the Fisher information is the total entropy production. Using the equality condition of the Cramér-Rao inequality, we find that the stochastic total entropy production is the only quantity which can attain equality in the thermodynamic uncertainty relation. Furthermore, we apply the Chapman-Robbins inequality and obtain a relation for the lower bound of the ratio between the variance and the sensitivity of systems in response to arbitrary perturbations.

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Design principles for enhancing phase sensitivity and suppressing phase fluctuations simultaneously in biochemical oscillatory systems

Cited by 46 publications

References 52 publications

Irreversibility in dynamical phases and transitions

Irreversibility in dynamical phases and transitions

The thermodynamic uncertainty relation in biochemical oscillations

Uncertainty relations in stochastic processes: An information inequality approach

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