Genetic Toggle Switch without Cooperative Binding

Lipshtat, Azi; Loinger, Adiel; Balaban, Nathalie Q.; Biham, Ofer

doi:10.1103/physrevlett.96.188101

Cited by 180 publications

(193 citation statements)

References 26 publications

(26 reference statements)

Supporting

Mentioning

183

Contrasting

Order By: Relevance

“…We introduce the cooperativity in repressor-DNA binding by allowing the active repressor to bind two binding sites with occupation-dependent binding affinity (r > 1). Notice, however, that cooperativity is not a necessary condition for the toggle behavior [10]. Following mass-action kinetics, the dimensionless parameters can be represented by equilibrium constants:…”

mentioning

confidence: 99%

Two-Component Genetic Switch as a Synthetic Module with Tunable Stability

Ghim

Almaas

2009

Phys. Rev. Lett.

View full text Add to dashboard Cite

Despite stochastic fluctuations, some genetic switches are able to retain their expression states through multiple cell divisions, providing epigenetic memory. We propose a novel rationale for tuning the functional stability of a simple synthetic gene switch through protein dimerization. Introducing an approximation scheme to access long-time stochastic dynamics of multiple-component gene circuits, we find that the spontaneous switching rate may exhibit greater than 8 orders of magnitude variation. The manipulation of the circuit's biochemical properties offers a practical strategy for designing robust epigenetic memory with synthetic circuits. DOI: 10.1103/PhysRevLett.103.028101 PACS numbers: 87.18.Cf, 05.40.Ca, 82.39.Àk One of the most significant challenges in cell biology of the postgenome era is to understand how the functional repertoire of cells is related to system-level properties of complex signaling networks. The suggestion that cellular networks are organized around functional modules [1] has led the way for large-scale studies of their organizing principles [2]. A particularly important class of functional modules is able to behave as bistable switches, providing a cell with the ability to change between two discrete behavioral states. In general, the bistable behavior allows cells to retain information about transient intracellular signals for many generations [3], thus serving as epigenetic ''memory'' devices. For instance, the lambda phage toggle is capable of sustaining its lysogenic reproduction mode for $10 7 generations before spontaneously exiting [4]. This is an impressive feat, as transitions between the different states of a toggle can be driven by fluctuations in the abundance of its constituting proteins. Furthermore, by tuning the toggle's spontaneous switching rate, it is possible to generate phenotypic diversity in populations that matches fluctuations in nutrient availability [5], thus providing a directly measurable fitness effect.Recently a simple toggle switch consisting of a pair of transcriptionally repressing genes was constructed [6], demonstrating the feasibility of de novo synthesis of cellular memory units. Scalable strategies for integrating the toggle as part of gene circuits with more elaborate functionalities, however, critically relies on the quantitative understanding of the toggle's capacity to generate robust yet tunable switching behavior. Here we identify key factors that modulate the stability of various genetic toggle switches and propose a novel method that is based on the manipulation of fast binding-unbinding dynamics among proteins, DNA, and other macromolecules.To quantitatively evaluate the toggle's robustness against random fluctuations and its dependence on circuit topology and kinetic details, we use the chemical master equation. We have identified experimentally tunable parameters and evaluated their effects on the switching rate.For biologically relevant parameter choices [7], we find that the switching rate can be tuned over a range of more than...

show abstract

mentioning

confidence: 99%

Two-Component Genetic Switch as a Synthetic Module with Tunable Stability

Ghim

Almaas

2009

Phys. Rev. Lett.

View full text Add to dashboard Cite

show abstract

“…However, the small size of the aerosol particles and the low density of some of the reactive species may require stochastic methods. Another example is genetic networks in cells and bacteria [63,64,65,66]. These networks describe the process of protein synthesis and its regulation.…”

Section: Discussionmentioning

confidence: 99%

Efficient stochastic simulations of complex reaction networks on surfaces

Barzel

Biham

2007

The Journal of Chemical Physics

Self Cite

View full text Add to dashboard Cite

Surfaces serve as highly efficient catalysts for a vast variety of chemical reactions. Typically, such surface reactions involve billions of molecules which diffuse and react over macroscopic areas.Therefore, stochastic fluctuations are negligible and the reaction rates can be evaluated using rate equations, which are based on the mean-field approximation. However, in case that the surface is partitioned into a large number of disconnected microscopic domains, the number of reactants in each domain becomes small and it strongly fluctuates. This is, in fact, the situation in the interstellar medium, where some crucial reactions take place on the surfaces of microscopic dust grains. In this case rate equations fail and the simulation of surface reactions requires stochastic methods such as the master equation. However, in the case of complex reaction networks, the master equation becomes infeasible because the number of equations proliferates exponentially.To solve this problem, we introduce a stochastic method based on moment equations. In this method the number of equations is dramatically reduced to just one equation for each reactive species and one equation for each reaction. Moreover, the equations can be easily constructed using a diagrammatic approach. We demonstrate the method for a set of astrophysically relevant networks of increasing complexity. It is expected to be applicable in many other contexts in which problems that exhibit analogous structure appear, such as surface catalysis in nanoscale systems, aerosol chemistry in stratospheric clouds and genetic networks in cells.

show abstract

“…These effects can be expected to propagate to the network level. For example, in genetic switches, where stochastic fluctuations in protein numbers determine, among other factors, the switching frequency [10,11], cooperative binding of the proteins enhances the range of conditions for which bistability is observed [12]. …”

Section: Introductionmentioning

confidence: 99%

Effects of multimerization on the temporal variability of protein complex abundance

et al. 2013

View full text Add to dashboard Cite

We explore whether the process of multimerization can be used as a means to regulate noise in the abundance of functional protein complexes. Additionally, we analyze how this process affects the mean level of these functional units, response time of a gene, and temporal correlation between the numbers of expressed proteins and of the functional multimers. We show that, although multimerization increases noise by reducing the mean number of functional complexes it can reduce noise in comparison with a monomer, when abundance of the functional proteins are comparable. Alternatively, reduction in noise occurs if both monomeric and multimeric forms of the protein are functional. Moreover, we find that multimerization either increases the response time to external signals or decreases the correlation between number of functional complexes and protein production kinetics. Finally, we show that the results are in agreement with recent genome-wide assessments of cell-to-cell variability in protein numbers and of multimerization in essential and non-essential genes in Escherichia coli, and that the effects of multimerization are tangible at the level of genetic circuits.

show abstract

Genetic Toggle Switch without Cooperative Binding

Cited by 180 publications

References 26 publications

Two-Component Genetic Switch as a Synthetic Module with Tunable Stability

Two-Component Genetic Switch as a Synthetic Module with Tunable Stability

Efficient stochastic simulations of complex reaction networks on surfaces

Effects of multimerization on the temporal variability of protein complex abundance

Contact Info

Product

Resources

About