Design principles of biochemical oscillators

Novák, Béla; Tyson, John J.

doi:10.1038/nrm2530

Cited by 1,052 publications

(1,167 citation statements)

References 67 publications

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“…S3A) reveals that the negative feedback loop alone (i.e. with two interactions) cannot sustain oscillations; a fact also shown in previous studies (Ferrell et al 2011;Novak and Tyson 2008;Lomnitz and Savageau 2014). In our simulations, only three two-component configurations are able to oscillate (Supplementary Fig.…”

Section: Motifs For Oscillatory Behaviorsupporting

confidence: 85%

“…Several studies have made contributions towards identifying some design principles for oscillatory behaviour. Network motifs-recurrent patterns of interactions believed to form the building blocks of any complex network (Milo et al 2002;Yeger-Lotem et al 2004;Barabasi and Oltvai 2004;Alon 2007;Kim et al 2010)-have also been highlighted to some extent for oscillators (Ferrell et al 2011;Wagner 2005;Novak and Tyson 2008;Tsai et al 2008;Burda et al 2011;Lomnitz and Savageau 2014;Noman et al 2015;Semenov et al 2015).…”

Section: Introductionmentioning

confidence: 99%

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Design principles for robust oscillatory behavior

2015

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Oscillatory responses are ubiquitous in regulatory networks of living organisms, a fact that has led to extensive efforts to study and replicate the circuits involved. However, to date, design principles that underlie the robustness of natural oscillators are not completely known. Here we study a three-component enzymatic network model in order to determine the topological requirements for robust oscillation. First, by simulating every possible topological arrangement and varying their parameter values, we demonstrate that robust oscillators can be obtained by augmenting the number of both negative feedback loops and positive autoregulations while maintaining an appropriate balance of positive and negative interactions. We then identify network motifs, whose presence in more complex topologies is a necessary condition for obtaining oscillatory responses. Finally, we pinpoint a series of simple architectural patterns that progressively render more robust oscillators. Together, these findings can help in the design of more reliable synthetic biomolecular networks and may also have implications in the understanding of other oscillatory systems.

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Section: Motifs For Oscillatory Behaviorsupporting

confidence: 85%

Section: Introductionmentioning

confidence: 99%

Design principles for robust oscillatory behavior

2015

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“…In the experimental work of Danino et al [22] a GRN comprised of three genes was introduced into bacterial cells and allowed for oscillations to exist due to the presence of activation-inhibition feedback loops part of the GRN [21,[24][25][26][27][28][29]. As shown in figure 1 these genes are, luxI, aiiA and yemGFP and all are under the influence of the same promoter, li-P [22].…”

Section: The Spatiotemporal Model With Controlmentioning

confidence: 99%

“…In the experimental work [22], a synthetic genetic regulatory network (GRN) based on a quorum sensing (QS) architecture [23] was introduced into E.coli cells found within a microfluidic chamber. This GRN had activation-inhibition feedback loops, which lead to oscillatory behaviour [24][25][26][27][28][29], and also allowed for the production of a small hormone molecule referred to as an autoinducer that was freely exchanged between cells and their environment leading to an all-to-all coupling across members of the population. The result was synchronised population-wide oscillations in the metabolic states of cells, witnessed with the help of green fluorescent protein (GFP) whose induction relied on the GRN dynamics.…”

Section: Introductionmentioning

confidence: 99%

Entrainment and Control of Bacterial Populations: An in Silico Study over a Spatially Extended Agent Based Model

Mina¹,

Tsaneva-Atanasova

Bernardo

2016

ACS Synth. Biol.

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General rightsThis document is made available in accordance with publisher policies. Please cite only the published version using the reference above. Full terms of use are available: http://www.bristol.ac.uk/pure/about/ebr-terms AbstractAs control in cellular populations is becoming more common we extend a spatially explicit agent based model (ABM), developed previously to investigate population emergent behaviour of synchronized oscillating cells in a microfluidic chamber, to include control. Thus, unlike most of the work in models that deal with control of biological systems, we model individual cells with spatial dependencies that may contribute to certain behavioural responses. We use the model to test whether linear control methods can be used to tame the collective behaviour of a bacterial population as recently suggested in the literature. We compare and contrast open and closed loop control in a spatially explicit model of control (specifically proportional control (P-control), proportional-integral control (PI-control) and proportional-integral-derivative control (PID-control) as can be applied in a microfluidic chamber setting) and show when entrainment to a non-natural oscillating period is possible, using an increasing bacterial population size. Results indicate that during open loop control entrainment is only possible in a subset of forcing periods, unlike closed loop control, and a wide variety of dynamical behaviours is obtained outside the regions of entrainment which in a physical setting may be undesirable. However, even with closed loop control, fixed gains cannot harness a population that keeps growing beyond a certain size.

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“…In addition, it is often attractive to reduce the dimensionality by formulating the models in the limit of many molecules, in which the average concentration of molecules can be modelled with differential equations 7 . In these limits, it is well known that the delayed feedback may result in large amplitude oscillations 8,9 , where the feedback system is out of phase with species it is trying to regulate. Such delay-induced oscillations are, for example, believed to drive specific molecular clocks 10,11 .…”

mentioning

confidence: 99%

Delay-induced anomalous fluctuations in intracellular regulation

2011

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Direct negative feedback decreases fluctuations and is a ubiquitous mechanism for homoeostatic control. However, intracellular regulation frequently operates indirectly, resulting in delayed responses. Here we derive an analytical expression that quantifies the consequences from delayed negative feedback resulting from typical multistep synthesis pathways, for example, transcription or translation. We find that indirect feedback leads to more fluctuations than without feedback for intermediate delays, but surprisingly not for long delays. The anomalous fluctuations at intermediate delays emerge from positive correlations between the delayed regulatory events, and are shown to be equivalent to an increased stoichiometry in the synthesis of new molecules. The results primarily give us insight about the design principles of delayed stochastic control systems and why a fixed feedback delay gives more fluctuations than a broadly distributed feedback delay. It is also shown that the feedback delay of autorepressed regulators can result in more sensitive regulation of downstream processes through stochastic focusing.

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Design principles of biochemical oscillators

Cited by 1,052 publications

References 67 publications

Design principles for robust oscillatory behavior

Design principles for robust oscillatory behavior

Entrainment and Control of Bacterial Populations: An in Silico Study over a Spatially Extended Agent Based Model

Delay-induced anomalous fluctuations in intracellular regulation

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