The Macroscopic Effects of Microscopic Heterogeneity in Cell Signaling

Mugler, Andrew; Wolde, Pieter Rein ten

doi:10.1002/9781118571767.ch5

Cited by 11 publications

(13 citation statements)

References 89 publications

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“…This probability gradually decreases as the radial separation increases. In general, the partners could rebind multiple times before they reach a radial separation large enough that they can be experimentally detected as unbound 15 , 16 .…”

Section: Resultsmentioning

confidence: 99%

A general mechanism for competitor-induced dissociation of molecular complexes

et al. 2014

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The kinetic stability of non-covalent macromolecular complexes controls many biological phenomena. Here we find that physical models of complex dissociation predict that competitor molecules will in general accelerate the breakdown of isolated bimolecular complexes by occluding rapid rebinding of the two binding partners. This prediction is largely independent of molecular details. We confirm the prediction with single-molecule fluorescence experiments on a well-characterized DNA strand dissociation reaction. Contrary to common assumptions, competitor–induced acceleration of dissociation can occur in biologically relevant competitor concentration ranges and does not necessarily implyternary association of competitor with the bimolecular complex. Thus, occlusion of complex rebinding may play a significant role in a variety of biomolecular processes. The results also show that single-molecule colocalization experiments can accurately measure dissociation rates despite their limited spatio temporal resolution.

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Section: Resultsmentioning

confidence: 99%

A general mechanism for competitor-induced dissociation of molecular complexes

et al. 2014

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“…The problem arises when we want to connect eqn (33) to the expression used in TIS/FFS to compute the dissociation rate in the case that the distribution at s is not isotropic. The principal idea of the scheme presented in Sections 4 and 5 is that P(r n |s), as obtained in a TIS/FFS computation of the dissociation rate, is given by the analytical result k D (s)/(k a (s) + k D ), for r n / N. We could thus use this analytical result to obtain the intrinsic rate k a (s) in eqn (13) and (14); the expression that relates P(r n |s) to k a (s) when r n is nite, is eqn (20). However, in the case of anisotropic interaction potentials the distribution of reactive trajectories at the s interface can also become anisotropic.…”

Section: Anisotropic Interactionsmentioning

confidence: 99%

“…In fact, it is now becoming increasingly recognized that cells exploit the spatial heterogeneity of micro-domains, lipid ras, clusters, and scaffolds as a computational degree of freedom for enhancing information transmission. 13,14 Modeling the reactions in these spatially heterogeneous systems oen requires knowledge of the intrinsic rate constants. Last but not least, for simulating association and dissociation reactions in 1D and 2D, knowledge of the intrinsic rate constants is even more pertinent, because no well-dened effective rate constant exists in the long-time limit.…”

Section: Introductionmentioning

confidence: 99%

The intrinsic rate constants in diffusion-influenced reactions

Bolhuis

Wolde

2016

Faraday Discuss.

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Intrinsic rate constants play a dominant role in the theory of diffusion-influenced reactions, but usually as abstract quantities that are implicitly assumed to be known. However, recently it has become clear that modeling complex processes requires explicit knowledge of these intrinsic rates. In this paper we provide microscopic expressions for the intrinsic rate constants for association and dissociation processes of isotropically interacting particles and illustrate how these rates can be computed efficiently using rare event simulations techniques. In addition, we address the role of the orientational dynamics, for particles interacting via anisotropic potentials.

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“…Because rebindings are so much faster than bulk arrivals, they can be integrated out [46,56,84]. Exploiting that rebinding interference can be neglected, the probability that a particle that has just dissociated from the receptor will rebind the receptor rather than diffuse away into the bulk is…”

Section: Role Of Rebindingmentioning

confidence: 99%

Fundamental Limits to Cellular Sensing

et al. 2016

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In recent years experiments have demonstrated that living cells can measure low chemical concentrations with high precision, and much progress has been made in understanding what sets the fundamental limit to the precision of chemical sensing. Chemical concentration measurements start with the binding of ligand molecules to receptor proteins, which is an inherently noisy process, especially at low concentrations. The signaling networks that transmit the information on the ligand concentration from the receptors into the cell have to filter this receptor input noise as much as possible. These networks, however, are also intrinsically stochastic in nature, which means that they will also add noise to the transmitted signal. In this review, we will first discuss how the diffusive transport and binding of ligand to the receptor sets the receptor correlation time, which is the timescale over which fluctuations in the state of the receptor, arising from the stochastic receptor-ligand binding, decay. We then describe how downstream signaling pathways integrate these receptor-state fluctuations, and how the number of receptors, the receptor correlation time, and the effective integration time set by the downstream network, together impose a fundamental limit on the precision of sensing. We then discuss how cells can remove the receptor input noise while simultaneously suppressing the intrinsic noise in the signaling network. We describe why this mechanism of time integration requires three classes (groups) of resources-receptors and their integration time, readout molecules, energy-and how each resource class sets a fundamental sensing limit. We also briefly discuss the scheme of maximum-likelihood estimation, the role of receptor cooperativity, and how cellular copy protocols differ from canonical copy protocols typically considered in the computational literature, explaining why cellular sensing systems can never reach the Landauer limit on the optimal trade-off between accuracy and energetic cost.B Pieter Rein ten Wolde tenwolde@amolf.nl

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The Macroscopic Effects of Microscopic Heterogeneity in Cell Signaling

Cited by 11 publications

References 89 publications

A general mechanism for competitor-induced dissociation of molecular complexes

A general mechanism for competitor-induced dissociation of molecular complexes

The intrinsic rate constants in diffusion-influenced reactions

Fundamental Limits to Cellular Sensing

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